Sleep patterns and avoidance conditioning in the rat

Physiology and Behavior, Vol. 14, pp. 329--335. Brain Research Publications Inc., 1975. Printed in the U.S.A.

Sleep Patterns and Avoidance Conditioning in the Rat JEAN DELACOUR 1 AND JEAN BRENOT 2

Laboratoire de Psychophysiologie, Universit~ Paris VII, 7 quai Saint-Bernard, Bat. B. 75005. Paris, France

(Received 17 July 1974) DELACOUR, J. AND J. BRENOT. Sleep patterns and avoidance conditioning in the rat. PHYSIOL. BEHAV. 14(3) 329-335, 1975. - For 19 male rats of the Wistar strain, percentages of wakefulness (W), slow sleep (SS) and paradoxical sleep (PS) were determined by.recording EEG activity of neo-cortex and EMG of neck muscles, for 48 consecutive hours. After the recording periods, the locomotor activity of the animals was measured in an open-field; then they were trained in a two-way shuttle-box. Statistical analysis showed significant correlations between physiological and behavioral variables. The most interesting correlation was that between percentage of PS and number of shocks received during avoidance conditioning: r = -0.521. Number of shocks was also significantly correlated with the ratio PS/W (r = -0.567). On the contrary, percentages of W and SS were not significantly correlated with learning scores. Multivariate analysis of the data showed a direct relationship between PS, avoidance and activity scores. These results may reflect a relationship between individual patterns of central activation and shuttle-box situation as well as a direct involvement of PS in memory processes. Rat

Patterns of sleep

Paradoxical sleep

Avoidance conditioning

Open-field activity

or 6 to a cage before the experiment. A t surgery, they weighed 2 2 0 - 2 7 0 g. Animals were anesthetized w i t h P e n t h o t a l (70 mg/kg, IP) following which two pairs of cortical electrodes were placed on the dura mater, positioned symmetrically a b o u t the midline: one pair at bregma, the other, at lambda. These electrodes were m a d e from silver wire of 0.3 m m dia., flattened at the end in contact with the dura. A third pair of electrodes, made of a loop of silver wire soldered to a flexible insulated wire, was placed u p o n the neck muscles but not fastened to them. The three pairs of electrodes were soldered to a microc o n n e c t o r fastened to the skull by dental cement. A f t e r surgery, the animals were allowed to recuperate for at least one week, following which animals entered the first phase of the experiment. During the period of recuperation as well as the experiment, animals were housed individually and weighed every day e x c e p t during periods of recording.

R E L A T I O N S H I P S b e t w e e n so called paradoxical sleep and l e a r n i n g p h e n o m e n a have received s o m e measure o f empirical c o n f i r m a t i o n [6, 7, 19]. In rats, paradoxical sleep deprivation can affect r e t e n t i o n as well as learning [ 1 5 ] ; conversely, learning is s o m e t i m e s followed by increased paradoxical sleep [16]. Until recently, little experimental a t t e n t i o n has been given to the possible i m p o r t a n c e of individual patterns of sleep-waking cycles for learning p h e n o m e n a . Results of a preliminary investigation [4] suggest that significant relationships can be u n c o v e r e d by this approach; the present study was u n d e r t a k e n to confirm and e x t e n d these preliminary observations. The experimental design was briefly as follows: percentages of paradoxical sleep (PS), slow wave sleep (SS) and waking (W) were d e t e r m i n e d for each animal of an h o m o g e n e o u s group of rats, over an entire sleep-waking cycle. Following this d e t e r m i n a t i o n , each animal was trained on an active avoidance task. A f t e r training, percentages of PS, SS and W were again measured u n d e r conditions similar to the first recording conditions, in order to confirm the stability of the individual sleep-waking patterns. The relationships b e t w e e n these patterns and p e r f o r m a n c e during learning were studied statistically with a multivariate analysis c o n d u c t e d by c o m p u t e r .

Procedure Phase L Animals were individually placed in a square box measuring 60 × 60 cm, o f which the floor was divided into 9 squares measuring 20 x 20 cm. During a period of 10 min, record was kept of the n u m b e r of squares crossed by the animal, as well as the n u m b e r of defecations. The apparatus was illuminated by a 40 W bulb placed one meter above its center and was placed in a s o u n d p r o o f cabinet measuring a p p r o x i m a t e l y 1 m 3 Observations were made by

METHOD

Animals Animals were 25 male rats of the Wistar strain, housed 5

.

~Requests for reprints should be sent to J. Delacour, Laboratoire de Psychophysiologie, Universit6 de Paris VII, 7 quai Sant-Bernard, Bat. B. 75005, Paris, France. 2 Centre d'Etudes Nucl6aires, D6partment de Protection, 92260, Fontenay, France. 329

330 means of closed-circuit television. A ventilating apparatus provided a background noise of 70 to 77 db above human threshold. All measurements were made between 12:00 and 14:00 hours. Phase lI. Animals were placed into individual cages in the recording room for 24 hr. Following this period of adaptation, the male half of the micro-connector, linked to the recording apparatus, was connected to the animals's head. There followed another adaptation period, of at least 24 hr, during which adjustements were made, such as the length and tension of the recording wires fastened to the animal's head. At the end of this period, the electrocorticogram (ECG) and the electromyogram (EMG) of the neck muscles were continually recorded upon a pen recorder during at least two 24 hr periods. Recording cages were constructed of opaque plastic, with one Plexiglas wall which permitted observation. The dimensions were 30 x 30 x 50 cm (height). The recording wires were connected to the recording apparatus by means of a rotary mercury connector which served to diminish movement artifacts and permitted free movement of the animal. Water and standard dry food were always available ad lib. Four identical recording cages were used, each approximately 2.5 meters away from the two 100 W bulbs used to illuminate the recording room. The light-dark cycle of the recording room was identical to that of the animal quarters (illuminated 8 : 0 0 - 2 0 : 0 0 ) . It should be noted that the level of illumination in the animal quarters varied considerably according to the location of the cage. Temperature in the recording room was kept equivalent to that in the animal quarters (23 ° -+ 2°C) by an air conditioner. Access to the recording room was strictly limited to the periodic visits of the experimenters (usually without effect on behavior or EEG of the animals) and a rapid cleaning of the cages each morning. The noise of the air conditioner served to mask extraneous noises such as those produced by the recording apparatus. However, noises produced by the animals were very probably perceived by neighboring animals, but these noises were part of the normal acoustic background of the animal quarters. At the end of this recording period, the animals were returned to the animal quarters for a readaptation period of 48 hr. Following this, they were again tested in the open-field situation described in Phase I. Phase IH. Following the readaptation period, animals were trained in an avoidance task, the two-way shuttle-box avoidance. The experimental apparatus consisted of a Plexiglas cage measuring 60 x 30 x 50 cm high, divided into two compartments (30 x 30) by a barrier 5 cm high. The floor and the barrier were made of brass bars 4 mm in. dia., separated by 15 mm. Each compartment was equipped with a 15 W bulb fastened to the end wall approximately 35 cm above the floor. The apparatus was placed into a soundproof box identical to that used for the open-field test. Programming and recording apparatuses were located in an adjoining room and the animal was observed by means of closed-circuit television. Two shuttle-boxes, located in two different cabinets, permitted testing of two animals simultaneously. Animals ,"ere first habituated to the experimental apparatus by free exploration for 5 min during 5 consecutive days, during which time no stimuli were presented. Following this period, training began and continued for 10 days. Each training session took place between 11:30 and 14:30 hours and consisted of 30 trials separated by a mean interval of 30 sec (range from 15 to 60 sec). The signal was the

I)ELACOUR AND BRENOT simultaneous illumination of the two bulbs tastened Io the interior of the apparatus. Five sec after presentation of the signal, an electric shock of 1.0 mA was delivered to the floor and the barrier by means of a scrambler-equipped generator. A complete crossing of the barrier during the signal-shock interval terminated the signal and no shock was delivered (avoidance response). Crossings made more than 5 sec after signal onset ended the signal and tile shock simultaneously. Maximum shock duration was 10 sec. Each animal received l 0 training sessions regardless of its performance. Phase II/. Ten days after the completion of training, EEG and EMG were again recorded for each animal in exactly the same manner as in Phase II. Analysis of EEG and EMG recordings distinguished three waking-sleep states according to the usual criteria [18, 23, 27] employed in the study of sleep in rats: waking (W), slow wave sleep (SS) and paradoxical sleep (PS). Each minute of the animals' records was classed according to the state occupying the greatest portion of that minute. When the first half of the minute was continuously occupied by one behavioral state and the second half, by another, one half minute was attributed to each state. All scoring was done by the same judge. At intervals between 10:00 and 17:00 hours, animals were directly observed and the behavioral state directly noted alongside the EEG and EMG: this procedure provided a key for interpreting this recording, permitting acurate assessment of waking-sleep state during those periods when behavioral state was not directly observed. Approximately one percent of randomly selected recordings were analyzed by a second judge ; the correlation coefficient between the scores of the two judges was r = + 0.893. Analysis was usually done on data from the second recording day, both before and after the training period. Six animals were discarded because of failure to obtain good records. Data Analysis. Eight measurements were made on each of the 19 animals retained: AC, mean activity score during the two open field sessions (Phase I and II); SH, number of shocks received by each animal during the 10 training sessions of Phase III; E-l, SS-I, PS-1, E-2, SS-2, PS-2, percentages of waking, slow wave sleep and paradoxical sleep, respectively during the first recording session (Phase II) and the second recording session (Phase IV). These 8 variables were first analyzed separately: histograms were constructed, means and standard deviations were calculated. Linear correlation coefficients were then calculated. These are interpretable only if the sample is homogeneous, that is there are no subgroups among the animals that differ systematically from the population with respect to the experimental variables. In order to assess this assumption of homogeneity in the present case, the technique of Principal Component Analysis was employed. This multidimensional analysis technique presupposes that the variables are quantitative - as in the present case and permits a representation of the differences between animals in terms of these variables; these differences are expressed by an arbitrarily chosen distance. This descriptive technique permits: (1) The regrouping into the same classes of animals similar with respect to the experimental variables. This similarity is expressed in terms of the initially chosen distance. (2) The regrouping of experimental variables into classes of highly correlated variables. The principle of this technique is, briefly, as follows: each animal is represented as a point in a space of p dimen-

SLEEP AND AVOIDANCE CONDITIONING

331

sions, by p coordinates: X~ . . . . X~, where X~ is the value of the jth variable for animal i. The constellation of points generated by the group of animals represents all pertinent information but it is not readily conceptualized and it cannot be visualized. To permit visualization, the initial data are projected into a space of two or three dimensions where the loss of information is minimal, that is where the respective initial positions of the subjects are best preserved. For this purpose, the Principal Component Analysis selects the directions along which the dispersion of the subjects is maximal. These directions define the principal axes of the two or three dimensional space; the coordinates of all the animals along the principal axes constitute the principal components. The relative importance of each of the principal axes is assessed by the percentage of total interindividual variability it represents. Correlations are calculated between the principal components and the initial variables. These correlations are graphically represented by a circle of correlations in which the coordinates of a given initial variable are its correlations with the principal components. This circle aids in the interpretation of the principal components but also helps to visualize the correlations between the initial variables themselves. For further details, see Anderson [ 1 ].

TABLE 1 MEAN PERCENTAGES OF W, SS AND PS

Mean Values of Initial Variables

Stability of Sleep-waking Measures Although PS measures remained quite stable over the two recording sessions, the total duration of W was significantly shorter during the second session than during the first, and that of SS, significantly longer as assessed by the

SD

W-1

38.91

5.23

W-2

34.76

6.64

51.60

5.30

SS-2

56.12

6.91

PS-1

9.49

1.43

PS-2

9.11

1.22

Correlations Between the Initial Variables Table 2 shows the correlation matrix of the 8 measures made on the subjects: number of shocks received by the animals in the shuttle-box (SH); activity scores in the openfield situation (AC); percentages of W, SS and PS during the first recording session (W-l, SS-1 and PS-1) and during the second recording session (W-2, SS-2 and PS-2). Analysis of this table can be facilitated by considering the following sub-groups: Correlations between W, SS and PS. High correlations (p<0.01) between W-1 and W-2, SS-1 and SS-2, PS-1 and PS-2, suggest stable patterns of sleep-waking. Within a

CORRELATION MATRIX OF INITIAL VARIABLES SH

W-1

SD

SS-1

TABLE 2

AC

Mean

Wilcoxon test (p<0.01). In spite of these variations, high correlations were obtained between the data of the first recording session and those of the second: + 0.776 for W measures, + 0.789 for SS measures and + 0.794 for PS measures. These correlations reveal stable individual patterns of sleep-waking. In fact, the durations of W and SS varied in the same direction for most animals, probably because of general factors such as the degree of habituation to the recording conditions. This stability of sleep-waking patterns in individual rats confirm the data of Webb [30] and is all the more remarkable since the two recording sessions were separated by an interval of at least four weeks, during which animals were trained in the shuttle-box. The number of electric shocks received by the animals varied considerably, ranging from 30 to 250; this variation could possibly have served to reduce the stability of the sleep-waking measures.

RESULTS

Table 1 gives the mean durations of PS, SS and W as percentages of total recording time, with standard deviations. The mean duration of PS was 1 min 53 sec (-+ 23 sec); that of SS was 6 min. 51 sec (-+ 71 sec) and that of W was 4 min 27 sec (+- 57 sec). During the 300 trials of the avoidance training, the mean number of shocks received by the animals was 148.26 (69.17). The mean activity score in the open-field situation was 26.74 (14.21). Defecation scores were too low to be of use.

Mean

SS-1

PS-1

W-2

SS-2

AC

1.00

SH

-0.52

W-1

-0.27

0.32

1.00

SS-1

0.18

-0.18

-0.86

PS-1

0.33

-0.52

-0.08

-0.19

1.00

W-2

-0.24

0.16

0.78

-0.75

-0.04

1.00

SS-2

0.16

-0.08

-0.78

0.79

-0.09

-0.88

1.00

PS-2

0.44

-0.42

0.21

-0.42

0.79

0.13

-0.30

PS-2

1.00 1.00

1.00

332

DELACOUR AND BRENOq

recording session, there is a high negative correlation between W and SS, while the other correlations are not significant. Correlations between behavioral variables AC and SH. A significant (p< 0.05) negative correlation exists between the number of shocks received by the animals during shuttle-box training and their activity in the open-field situation. Defecation scores were too low to be usable. Correlations between sleep-waking measures and behavioral variables. No significant correlations were found between the variable AC and any of the sleep-waking variables. The variable SH had no significant relation with W or SS, but a significant (p<0.05) negative correlation was found between SH and PS-I: r = - 0 . 5 2 . Between SH and PS-2, the correlation is in the same direction and attains the threshold p = 0.10 (r = - 0 . 4 2 ) .

Correlations Based upon Linear Combinations or Ratios o f W, SS and PS In addition to the original variables, variables of the form W + SS, W + PS, etc. or of the form W/SS, W/PS, etc. were considered. The only significant correlation between these new variables and the originals was the correlation between SH and the ratio PS-1]W-1, for which r reached - 0 . 5 7 (p<0.02). Figure 1 shows the constellation of points that represents this correlation. The correlation between SH and the ratio PS-2/W-2 attains the threshold p = 0.10 (r = -0.41 ). N sqocks

270~ 225-

then they should occupy neighboring positions in the plane: this is the case for Animals 17 and 7, for instance. Conversely, animals which are close to each other in the plane will have roughly similar scores across the five experimental variables, if the plane does in fact account for a high percentage of the interindividual variability. The distances between animals can be verified and interpreted by means of the histograms representing the distribution of the scores for each variable. In Fig. 2, the animals are differentiated along the direction defined by W-I and SS-I, which reflects the high negative correlation between these two variables. A second differentiation concerns the variables AC, SH and PS-1. With respect to these variables, two groups of animals can be distinguished, one consisting of animals (7, 17, 8, l 2, 3, 10) having low activity and paradoxical sleep scores associated with a high number of shocks, that is poor learning (Group a); the other group consists of animals (16, 1,4, 9, 5, 1 I, 14) having high activity and paradoxical sleep scores associated with a low number of shocks, that is high learning (Group b). The representation of Group b is somewhat obscured by the influence of variables W-I and SS-I: thus Animals 1 and 16 are separated from the rest of the group by their high scores on the variable W-1 and their low scores on the variable SS-1. Further, the Animals 13, not included in Group b because its average AC, SH and PS scores, is nonetheless quite close to certain animals of Group b, due to its high score on the variable SS-I and its low score on the variable W-I. However, inspection of the histograms of the variables AC, SH and PS-1 (Fig. 3) demonstrates the legitimacy of designating these two Groups a and b, if one disregards the influence of the variables W-1 and SS-1. These groups which distinguish 13 of 19 animals reflect the significant correlations between SH and AC ( - 0 . 5 2 ) and between SH and PS-1 ( - 0 . 5 2 t . • ]3]

150 -

;12

'; :1

619

";

I

i,

ii0

P5~I × 100 W1 • 15 ~

20

r

F

25

30

I

/I 0

A(}

WI

35

FIG. 1. Set of points representing the correlation between the ratio PS-1/W-I and the number of shocks received during avoidance training (r = -0.567).

\ 2~;71 1.$43

Results o f the Principal Component Analysis This analysis was performed on 5 of the initial 8 variables: AC, SH, W-l, SS-1 and PS-1. The variables W-2, SS-2 and PS-2 were disregarded, since these measurements were taken primarily to assure the stability of the sleep-waking patterns. The plane defined by the first two principal axes accounts for 80% of the total interindividual variability (Fig. 2). If 2 animals have similar scores across all 5 variables,

16

P51 a × ~ 1 (47%/

t.423

FIG. 2. Representation of the principal component analysis. The position of each animal is represented by that an arbitrarily attributed number. The arrows indicate the directions of the initial variables. Another form of representing the results was employed: the correlation circle (Fig. 4). In this circle, each initial variable takes as coordinates its correlations with the first two principal components. For example, the variable PS-I

SLEEP AND AVOIDANCE CONDITIONING

333 TABLE 3

AC

SH

59. O0

2 5 0 . O0

7. O0

30. O0

13, O0

55.00

Variable Max. Min.

c.w.

COMPARISON OF W, SS AND PS PERCENTAGES

PS 1 13.22 6.59

II

Matsumoto

Van Twyver

Delacour (Recording l)

W

48.0

44.80

38.91

SS

45.0

44.44

51.60

PS

7.0

10.76

9.49

1.66 19 18

18

14

t7 15

17

13

18

12

12

15

10

10

16

12

19

10

13

16

f16

11

8

8

15

8

11

14

14

9

7

17

6

11

7

4

6

9

S

2

19

6

7

5

9

3

2

5

I

4

I

13

3

3

2

1

I 4

K 6

Iii 2

I2!

I

rr' rrr iv

7

3

10

Class

I

II HI iv

Freq.

8

5

4

2

S

4

1

FIG. 3. Histograms representing the data of the initial variables AC, SH and PS-1. For each histogram, the maximal and minimal values of the distribution, the class width (C.W.)and the frequency of each class are indicated. Animals are represented by the same number as in Fig. 2.

I O,l c

@

E

8 0-

÷ eW1

-I

t, J

eAC

I

I

0

c(::~ponent

1

fl

FIG. 4. Correlation circle. The coordinates of each initial variable are the correlation coefficient of this variable with the two principal components.

has a correlation coefficient of + 0.384 with the first principal component, and of - 0 . 7 4 7 with the second principal component. These correlation coefficients are the coordinates of PS-1 within the circle; the coordinates for the other initial variables are determined in the same way. Inspection of the resulting positions shows again the opposition between the variables AC and PS-1 on the one hand, and SH on the other. One can see as well that these last three variables are more or less orthogonal to W-1 and SS-1,

which suggests that with few exceptions, the scores of paradoxical sleep, activity and learning are independent of the scores of waking and slow-wave sleep. DISCUSSION

Measures of Sleep-waking Variables The percentages of paradoxical sleep, slow-wave sleep and waking have different values, depending on the portion of the light-dark cycle in which the measures are taken. Thus comparisons between different experiments can be legitimately made only if these measures are based upon either the entire circadian cycle or upon identical portions of this cycle. Table 3 presents a comparison of sleep-waking percentages obtained by us during complete circadian cycles, with the results of Matsumoto [18] and Van Twyver [29], also based upon recordings made continually for at least 24 hours. There are many possible reasons for the differences observed in Table 3, as percentages of sleep and waking depend upon many factors. Some of these are related to the animals themselves (strain, age, sex, etc.); others are related to conditions of the environment: temperature [20, 22, 28], patterns of illumination [9,12], complexity of sensory stimulation from the environment [26]. It is difficult to evaluate the influence of these factors in our results. Among the conditions particular to our experiment, the most important is perhaps the following: the animals had attained, by the time of the first recording session, a relatively high level of tameness, having been handled every day since surgery, submitted to the preliminary spontaneous activity tests and habituated to the recording apparatus for at least 48 hours prior to the first recording session. This lengthy adaptation to the experimental conditions probably resulted in a reduction of emotional reactivity and exploratory activity, and might be at the origin of the relatively high percentage of slow-wave sleep and the relatively low percentage of waking. Another important point is the stability of individual waking-sleep patterns, as determined by high correlations between the data of the two recording sessions.

Relations Among the Variables The significant (p<0.05) negative correlation between the open-field activity scores and the number of shocks received by the animals during training, confirm a relation between these two variables that has already been reported [ 11,33], and apparently depends upon the emotional reactivity of the subjects [33]. The negative significant correlation between the number

334

DELACOUR AND BRENOT

of shocks and the percentage of PS or the ratio PS/W, can be interpreted as reflecting a relation b e t w e e n learning and the duration of paradoxical sleep phenomena. This relation can have several possible origins: (1) The acquisition of an avoidance response and the duration of paradoxical sleep may have a c o m m o n dependence u p o n a third variable such as for instance the cerebral catecholamines which play a crucial role in paradoxical sleep mechanisms [13]. A l t h o u g h clear causal relations have not yet been established, it appears that these three factors can covary significantly: acquisition of an active avoidance response is accompanied by a significant increase in the q u a n t i t y of brain norepinephrine (NE), [ 3 2 ] . According to H a r t m a n n [ 1 0 ] , paradoxical sleep deprivation reduces the q u a n t i t y of brain NE and slows active avoidance acquisition; administration of L-DOPA increases the q u a n t i t y of brain NE and suppresses the effects of PS deprivation on active avoidance learning: administration of a l p h a m e t h y l - p - t y r o s i n e slows avoidance learning while concurrently reducing the q u a n t i t y of brain NE and the duration of PS in rats [ 3 4 ] . T o the extent that the acquisition of avoidance responses involves u n c o n d i t i o n e d defensive reactions, it is interesting to note that repeated elicitation of these responses by stimulation of the lateral hypothalamus (in cats) is followed by a r e d u c t i o n of PS duration and of the q u a n t i t y of brain NE [ 21 ]. The relation b e t w e e n PS and SH could possibly, then, be based upon interindividual variations of some as yet undetermined third variable, possibly brain NE. In fact, as PS probably depends on the interaction of several neurochemical factors [ 1 4 ] , this third variable could be very complex. (2) A second broad category of explanation supposes a

causal relationship between PS and learning. For instance, several recent studies suggest that acquisition or retention of learning depend u p o n paradoxical sleep p h e n o m e n a [8, 16, 25], which could intervene in the phase of m e m o r y consolidation [2]. Paradoxical sleep p h e n o m e n a could also influence some aspects of learning by regulating the motivational state of the organism [ 5 ] ; more precisely, percentage of PS or the ratio PS/W could be an i m p o r t a n t characteristic of individual activation patterns. Activation patterns have been associated with learning [3, 17, 2 4 ] ; this relationship is frequently expressed by the Yerkes-Dodson law which is particularly applicable to motivation-learning relationships in rats, in the two-way shuttle-box [31]. Thus, w i t h o u t intervening directly in the i n f o r m a t i o n processing involved in learning p h e n o m e n a , PS could nevertheless play a role in the emotional adaptation of the organism during the course of avoidance learning. F u r t h e r data are necessary to more clearly establish the plausibility of these hypotheses. The progress of further research in this area will critically depend upon more complete measures of sleep-waking phenomena. Our results are based only upon the tonic aspects of PS, as manifested by the EMG of the neck muscles and the neo-cortical EEG. F u r t h e r m o r e , only the total q u a n t i t y of PS over the 24 hour period was considered. In the study of the relations b e t w e e n learning and individual sleep-waking patterns, it will be i m p o r t a n t to consider as well the phasic aspects of PS. Likewise, the distribution and the n u m b e r of PS episodes should be considered as possibly relevant variables. It will be also i m p o r t a n t to measure the manifestations of the PS p h e n o m e n a at the level of different brain structures which, like the hippocampus, may play a role in learning.

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