Cerebral and local cerebral metabolism in the cat during slow wave and REM sleep

Brain Research, 365 (1986) 112-124

112

Elsevier BRE 11430

Cerebral and Local Cerebral Metabolism in the Cat during Slow Wave and REM Sleep PETER RAMM and BARRIE J. FROST

Department of Psychology, Queen's University, Kingston, Ont. K7L 3N6 (Canada) (Accepted June 1lth, 1985)

Key words: sleep - - rapid-eye-movement (REM) sleep - - metabolism - - [14C]2-deoxyglucose

[14C]2-deoxyglucose autoradiography was used to show cerebral and regional cerebral metabolism during slow-wave sleep (SWS) and rapid-eye-movement sleep (REM) in the cat. Lower levels of mean cerebral metabolism, reflecting cerebral energy conservation, were associated with SWS. A clear link between REM and mean cerebral metabolism was not observed. At the regional level, SWS was associated with markedly low metabolism in thalamic sensory relays and in cortex. REM was associated with relatively low metabolism in the cerebellum, but with relatively high metabolism in the hippocampus, and in some 'motor' regions including the trigeminal and red nuclei. Thus, SWS was linked to cerebral energy conservation and to particularly low levels of functional activity in cortical and sub-cortical sensory regions. REM was unlike SWS in that: (a) REM did not appear to be strongly linked to cerebral energy conservation; (b) REM was linked to metabolism in fewer brain regions than was SWS; and (c) most REM-linked regions exhibited relatively high levels of metabolism. In addition, while SWS was most clearly associated with functional activity in sensory regions, REM was linked to functional activity in a small number of limbic and motor regions. In sum, SWS and REM are associated with distinctive cerebral metabolic and functional states. INTRODUCTION Energy metabolism is linked to functional activity in the central nervous system 70. Levels of cerebral energy metabolism can be shown with the [14C]2-deoxyglucose @4C]2-DG) technique. Therefore, some interest has focused upon possible increases in local cerebral glucose utilization ( L C G U ) during slowwave sleep 48. Such localized increases in metabolism could reflect functional activity linked'to sleep generation by 'hypnogenic centers'. However, organismic8,27,76 79, cerebral, and most local cerebral metabolic levels36, 48 are lower during slow-wave sleep (SWS) than during wakefulness. These findings have failed to support a theory of active sleep centers. Although rates of local metabolism do not increase during SWS, some brain regions in both the monkey 36,48 and rat 55 show unusual metabolic responses to sleep; responses which are unlike those of the cerebrum as a whole. That is, the effects of sleep upon cerebral metabolism vary from region to region, and metabolism in a limited n u m b e r of regions is more or less affected during sleep than is the m e a n level of ce-

rebral metabolism55. A region may become unusually active during sleep, relative to a lower mean level of cerebral metabolism. Alternatively, regional metabolism (and functional activity) may decrease more than mean brain metabolism. U n u s u a l metabolic responses may show brain regions with functions most strongly linked to sleep. A consistently higher or lower-than-average level of local metabolism during sleep could reflect functional activity linked to the generation of sleep phen o m e n a , or functional alterations resulting from sleep. These functional alterations could result from changes in any of the cerebral energy-dependent processes, including n e u r o n a l ionic homeostasis and excitability, and protein synthesis. If metabolic levels throughout the brain are mapped during each s l e e p - w a k e state, and then each regional level is compared with average brain metabolism, areas of unusual functional activity can be demonstrated. The areas of unusual functional activity may be generating sleep p h e n o m e n a , or may experience marked alterations in f u n d a m e n t a l biochemical processes during sleep. This report exam-

Correspondence: P. Ramm, Department of Psychology, Trent University, Peterborough, Ont. K9J 7B8, Canada. 0006-8993/86/$03.50© 1986 Elsevier Science Publishers B.V. (Biomedical Division)

113 ines levels of metabolic activity in the cat brain during wakefulness, SWS and REM, using [14C]2-DG as a marker for levels of metabolism. To show regions in which functional activity is markedly high or low during sleep, metabolism in specific cerebral regions is compared to the mean level of cerebral metabolism during each sleep state. MATERIALS AND METHODS Surgery Under pentobarbital anesthesia, twenty young male cats (0.9-1.7 kg) received parietal and occipital supradural electrodes. Stainless-steel wire electrodes were inserted into the neck muscles. All electrodes were terminated in a plastic strip, cemented to the skull with dental acrylic. The right jugular vein and carotid artery were cannulated. The free ends of the cannulas were led subcutaneously to a stainless-steel well, which was cemented to the skull just behind the electrode strip. The cannulas were regularly flushed with heparinized saline. At least 3 days were allowed for postsurgical recovery. During this period, the cats were observed for any behavioral or electrographic (based on 1 h/day of E E G recording) abnormalities resulting from the unilateral carotid cannulation. Only those animals exhibiting qualitatively normal behavior and a bilaterally symmetrical, normal E E G were selected for further participation. Behavioral states The recording and running chamber consisted of a plexiglass cage in which the animal could move about or lie outstretched. A gold slip-ring commutator and flexible wire connector permitted free movement and access to the cannulas via a feedthrough tube. White noise was present (70 dB spl) and lighting was synchronized to that in the cat colony (on at 09.00, off at 21.00 h). Of the 20 cats, 6 were REM-deprived by the water tank method. Eight to 12 h prior to the [~4C]2-DG run, each of these animals was placed on a round platform inside a bucket. Water came to within 2 cm of the platform surface. The platforms were sufficiently large to allow the animals to recline with their heads on their paws, and did not appear to cause much deprivation of SWS. The animals were able to

remain dry and appeared relatively comfortable during the REM-deprivation period. On the morning of the third postsurgical day, following 12 h of food deprivation, each cat was placed in the recording chamber and allowed to settle for approximately 1 h. Polygraphic recordings (10 ram/s) of E E G and EMG were made and continued throughout the [14C]2-DG run. The experimenter, in an adjacent room, had access to the cannulas via tubes (PE 50) which penetrated the wall. These tubes were short (approximately 2 m) to minimize their internal volume and permit relatively accurate sampling of arterial blood. Behavior was scored in 30-s epochs, each containing 1 of 5 categories of sleep-wake activity. Criteria for the categories of active wakefulness, quiet wakefulness, light SWS, deep SWS and REM have been described elsewhere -~5. Although all 5 of these state categories were scored, attention in this report centers on total SWS and REM. At approximately 11.00 h, 100 uCi/kg of [14C]2DG (American Radiolabelled Chemicals, 55 Ci/mol) was injected via the jugular cannula. The bolus of isotope was usually injected during quiet wakefulness or deep SWS. REM-deprived cats received the bolus during REM, but often left REM during the immediate postinjection period. Thus, REM-deprived cats did not cluster into a distinct (high REM) state group. Calculation of metabolic and relative metabolic activity Regional cerebral metabolic rates for glucose were measured with the quantitative autoradiographic deoxyglucose method 71. Blood samples (751tl) were obtained from the arterial cannula at 0.0, 0.5, 1, 2, 3, 4, 5, 10, 15, 20, 30 and 45 rain after injection. The blood samples were spun in an IEC MB centrifuge for 5 rain, and 25/xl aliquots of plasma were counted in a Searle Delta 300 scintillation counter. Counting efficiency was determined and quench correction was performed. Centrifuged blood samples taken at 0 and 45 rain were enzymatically assayed for plasma glucose 4~. After the 45 rain [14C]2-DG incubation period, the animals received a lethal dose of sodium pentobarbital via the arterial cannula. The brain was extracted and frozen in isopentane cooled to -40 °C. Cryostat

114 sections (20 ~tm) were cut at -16 °C, dried on hot slides (60 °C) and autoradiographs of tissue and [14C]methylmethacrylate standards (Amersham) were then prepared on Kodak X-TL film. Light transmission through the autoradiographs was read by computerized densitometry 56,57. Samples were taken from gray matter only. Local cerebral glucose utilization (LCGU), and mean cerebral glucose utilization (the sum of the L C G U values/number of regions sampled) were quantified in 14 of the 20 cats, using the regional brain 14C concentrations, the arterial plasma 14C curve and the arterial plasma glucose concentration (the plasma glucose assay was unavailable in 6 cats). The kinetic constants and lumped constant were those described for gray matter in the anesthetized cat 70. The mean cerebral glucose utilization values were used to obtain correlations between the general level of cerebral metabolism and each state. In addition, the correlations between regional metabolism and each sleep state were obtained. Analysis of the regional correlations did not require L C G U values. Instead, regional tissue equivalent isotope concentrations were analyzed. According to the operational equation for the [laC]2-DG method, isotope concentration is directly related to regional metabolic rate. For example, a region showing a glucose utilization rate twice the brain average will also show twice the average isotope concentration. Therefore, use of isotope concentration ratios yielded the same correlation coefficients as would be obtained from L C G U ratios, while allowing the inclusion of the 6 cats from which plasma glucose assays were unavailable. Also, the use of normalized metabolism values substantially reduced between animal variability. Finally, the ratios of local metabolism to mean brain metabolism have intuitive meaning. These are relative metabolic activity values, which reflect the extent to which a given region is like the rest of the brain during sleep. As we were looking for regions with marked metabolic linkage to sleep, the analysis of relative metabolic activity values was appropriate.

A utoradiographic sampling The regional anatomy of the cat brain was as defined by Berman5 and Berman and Jones 6. Each region was sampled bilaterally, usually in 3-6 sections. Spinal cord was sampled at the C2 level. Independent

samples were taken from superficial, medial and lateral sections of dorsal horn, from ventral horn and from regions surrounding the central canal. The most posterior sections of medulla were taken at P 18.3. From that level rostrally, a regular progression was taken at intervals of about 300/~m. Cerebellar cortex was sampled in the vermis and in dorsal portions at P 4.0-P 4.6. Entorhinal, parasubicular and visual cortices were sampled at A 6.4, auditory cortex in the suprasylvian region at A 10.2 and somatosensory cortex more dorsally at A 10.2. The hippocampus was sampled in its dorsal portions at A 4.8.

Calculation of the state value During the 45 min incubation period, the cat invariably exhibited more than one state. Animals could not be categorized as simply asleep or awake. Further, time spent in a state was n o t a n adequate measure of [14C]2-DG phosphorylated during that state. Because the amount of tissue [14C]2-DG available varied during the 45 min incubation period (Fig. 1), occurrence of a state at the beginning of the incubation period was more important than was later occurrence, when there was little [14C]2-DG available in tissue. For this reason, time spent in each state was converted to the proportion of injected [14C]2-DG available for phosphorylation during that state. The proportion of injected [14C]2-DG phosphorylated during a state (the state value) was obtained in 3 steps. First, the curve of plasma [14C] counts was converted to a curve of tissue [InC]2-DG concentration (Fig. 1), using the appropriate term from the operational equation for the [14C]2-DG method 71. Each point on the tissue [14C]2-DG curve represents the amount of tracer available for phosphorylation in gray matter at that moment in time. Then, the 45 min tissue [14C]2-DG curve was broken into ninety 30-s epochs and a state category (wake, SWS, REM) was assigned to each epoch. Finally, the times spent in each state were converted to state values, using the proportion of the area under the tissue [14C]2-DG curve occupied by each state. This proportional area is equivalent to the proportion of tissue [a4C]2-DG phosphorylated during the epochs containing a given state. Effectively, the state value measure weights each epoch in the 45 rain isotope incubation period by the importance of that epoch. The procedures we describe contain compromises,

115 ioral state. Correlations were also obtained for relative metabolic activity values in each cerebral region

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TIME (MINUTES) Fig. 1. Time-course of [t4C]2-deoxyglucose ([L¢C]2-DG) concentrations in arterial plasma and in gray matter during the 45 min

followinginjection of the label (cat 18). The plasma curve is derived from measurements of plasma [laC]2-DG concentration. The tissue value is calculated from the plasma curve and the mean values of kl*, k2* and K3* for gray matter in the anesthetized cat, according to the second term in the numerator of the operational equation for the 2-DG method. Note that the amount of [14C]2-DG available for phosphorylation is not constant. Most [14C]2-DG is available during the earl}' postinjection period. Therefore, animals are not scored only on the occurrence of a state, but by weighting each occurrence according to the tissue [14C]2-DG availability during that state. To perform this weighting, the total area under the tissue [14C]2-DG curve is calculated. Then, the proportion of the curve occupied by each state is calculated. The proportion of the curve area occupied by each state (closely equivalent to the proportion of [14C]2-DG phosphorylated in tissue during each state) is the state value. State times for this animal are awake 89% and SWS 11%. State values are awake 94% and SWS 6%.

necessary if the [IaC]2-DG method is to be used in situations containing multiple behavioral states. In particular, the weighting of epochs is subject to error arising from variability in the measured values of rate constants for bidirectional transport and phosphorylation of 2-DG during the early postinjection period 71. Error resulting from rate constant fluctuations has the effect of introducing some ' r a n d o m noise" into the state value measure. This noise makes it more difficult to observe subtle links between sleep and metabolism, but does not systematically bias the data. Our use of a large n u m b e r of animals is a compromise chosen to minimize the importance of rate constant errors, and to allow the use of correlational statistics.

The correlations Product-moment correlations (two-tailed) were obtained to describe the extent of linear relation between mean cerebral glucose utilization and behav-

during wakefulness, SWS and REM. Positive correlations reflect higher than average regional metabolism associated with a given state. A lack of correlation suggests that regional metabolism is inconsistently or non-linearh' associated with state, or responds to state in the same way as the brain as a whole. A negative correlation suggests that lower than average levels of regional metabolism are associated with a given state. A correlation of 0.5 or better has been arbitrarily chosen as indicating metabolic state-dependency (a relationship between metabolism and state). A correlation of 0.7 or better is considered strong. A correlation of 0.5 has P < 0.03 and a correlation of 0.7 has P < 0.001. These criteria do not apply to correlations between state values and mean cerebral glucose utilization. As mean glucose utilization values were only available for 14 of the 20 animals, a correlation of 0.5 is non-significant and a 0.6 criterion (P < 0.03) is used. RESULTS Mean cerebral glucose utilization (n = 14 cats, 150 brain regions/cat) was 70.46 umol/100 g/rain with an S.E.M. of 2.81. Cerebral glucose utilization was state-dependent. Lower levels of metabolism were associated with SWS (r -- -0.70, P < 0.005: awake r = 0.72). Levels of metabolism were not correlated with REM (r = -0.47, P < 0.09). This qualitative difference between SWS and R E M is somewhat ambiguous. The R E M and wake correlations differ significantly (Fisher z-test, P < 0,001), but the R E M and SWS correlations do not (Fisher z-test, P > 0.05). Thus, metabolism during R E M was unlike wakefulness and was not unlike SWS. However, the relationship between anv state and R E M metabolism was so weak that a significant correlation was not observed. To show brain areas with marked metabolic statedependency, we constructed ratios between local and mean cerebral metabolism in approximately 150 regions. Only those regions commonly linked to sleep or those constituting part of an anatomical system ex-

116 TABLE I

TABLE II

Association between state values and relative metabolic activity (local metabolic activity~mean brain metabolic activity) in the spinal cord and in aminergic nuclei

Association between state values and relative metabolic activity in the hypothalamic, medial thalamic and hippocampal regions

Relative metabolic activity is a measure of how regional metabolism is related to the average level of brain metabolism. Therefore, a positive or negative correlation indicates that higher or lower-than-average levels of regional metabolism are associated with a state. A correlation of 0.5 (P < 0.03) has been arbitrarily selected as significant. As SWS and wake are intercorrelated, the wake column is ignored. No aminergic region exhibits relative metabolism correlated with SWS or AS. Thus, aminergic regions exhibit the same metabolic association with sleep states as does the brain as a whole. Region Spinal cord Superficial dorsal horn Medial dorsal horn Lateral dorsal horn Ventral horn Periventricular gray Noradrenergic Locus coeruleus Parabrachial region Dopaminergic Ventral tegmentum Substantia nigra (pars compacta) Substantia nigra (pars reticulata) Serotonergic Posteropyramidal raphe n. Central inferior raphe n. Rostral granular raphe n. Central superior raphe n. Dorsal raphe n. N. linearis centralis

A wake SWS REM (product-moment correlations) 0.57 -0.15 -0.19 0.07 -0.09

-0.42 0.15 0.18 -0.07 0.25

-0.48 0.04 0.07 -0.02 -0.23

0.06 0.10

-0.14 -0.23

0.14 0.23

-0.33

0.30

0.16

-0.59

0.44

0.48

-0.05

0.08

-0.04

-0.42 -0.45 -0.39 0.23 -0.07 0.24

0.40 0.29 0.37 -0.25 0.08 -0.19

0.17 0.46 0.17 -0.03 0.02 -0.18

Region

A wake SWS REM (product-moment correlations)

Posterior hypothalamus Ventromedial hypothalamus Anterior hypothalamus Broca's band nuclei Preoptic region Centromedian thalamic n. Central lateral n. Mediodorsal n. Medioventral n. Rhomboid n. Ventral anterior n. Hippocampus: CA1 CA2 CA3/CA4 Pyramidal cell layer Stratum molecularelacunosum Dentate gyrus (molecular) Dentate gyrus (granular) Entorhinal cortex Parasubicular cortex

-0.21 -0.56 -0.5l -0.30 -0.33 0.04 0.40 0.47 -0.10 -0.08 0.28

0.19 0.67* 0.44 0.12 0.27 -0.10 -0.48 -0.54* 0.05 0.06 -0.38

-0.13 -0.05 -0.49 0.14

-0.01 -0.09 0.23 -0.25

0.32 0.30 0.68* 0.16

-0.10 -0.17 -0.32 -0.42 -0.28

-0.12 -0.08 0.05 0.12 0.07

0.46 0.54* 0.64* 0.67* 0.50*

0.10 -0.06 0.34 0.39 0.27 0.11 0.03 -0.02 0.13 0.07 0.04

* Achieves the criterion correlation of 0.5 (P < 0.03).

hibiting metabolic state-dependency are presented in Tables I - I V . As the state values for SWS and wake exhibit a strong intercorrelation (r = -0.86, P < 0.001), we usually limit our discussion to SWS and REM. SWS and R E M are i n d e p e n d e n t (r = 0.04, P < 0.87; isotope injection was timed to obtain this in-: dependence). No metabolic state-dependency was observed in the spinal cord or in the posterior medulla. In the pontine region, only the principal and motor nuclei of the trigeminal complex showed relative metabolism linked to REM. N o n e of the aminergic nuclei traditionally associated with state generation exhibited metabolic state-dependency (Table I). More rostrally, state-dependency was widespread in the medial thalamus, hypothalamus and hippo-

campus (Table II), in regions associated with sensory functions (Table III, Figs. 2, 3) and in regions linked to motor functions (Table IV, Fig. 4). Most state-dependent regions, in particular the sensory relays of the lateral thalamus, showed markedly low relative metabolism during SWS (Figs. 2, 3). Only the ventromedial hypothalamus showed high relative metabolism during SWS. R E M was linked to metabolism in some limbic and 'motor' regions. In most of these regions, relative metabolism was specifically linked to R E M and not to SWS. Significant correlations are evident during R E M (but not SWS) in cerebellar cortex (Fig. 4), the C A 3 - C A 4 and dentate regions of the hippocampus, the sensory and motor nuclei of the trigeminal nerve, the lateral division of the pontine gray, the red nucleus and in entorhinal cortex. We failed to observe localized areas of R E M - d e p e n d e n t functional activity in the pontomesencephalic reticular formation. DISCUSSION Sleep and cerebral metabolic rate f o r glucose O u r observation that SWS is associated with lower

117 TABLE III

TABLE IV

Association between state value and relative metabolic activity in regions associated with primary sensory functions

Association between state and relative metabolic activity in regions linked to motor functions

Region

Region

A wake SWS REM tproduct-moment correlations)

Gigantocellutar tegmental field Magnocellular tegmental field Central tegmental field Principle trigeminal n. Motor trigeminal n. Cerebel[ar cortex (granular) Cerebellar cortex (molecular) Red n. Substantia nigra (pars compacta) Substantia nigra (pars reticulata) Striatum

-0.16 -0.43 0.07 -0.51 0.48

0.01 0.32 -0.27 0.34 0.26

0.36 0.36 0.40 0.52* 0.51"

0.51

-0.28

-0.63*

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0.09 0.18

-0.25 0.58*

-0.59

0.44

0.48

0.05 -0.40

0.08 0.34

-0.04 0.25

Awake SWS REM (product-moment correlations')

Auditor 3,

Cochlear n. Superior olive Inferior colticulus Medial geniculate n. Auditory cortex (outer layers) Auditory cortex (layer IV) Auditory cortex (inner layers) Visual Medial pretectal n. Superior colliculus Lateral geniculate n. Pulvinar n. Visual cortex (outer layers) Visual cortex (layer IV) Visual cortex (inner layers) Olfactory Amygdaloid nuclei Prepyriform cortex Rhinal cortex Entorhinal cortex

-0.31 0.39 -0.13 0.78

0.39 0.54* 0.13 -0.79*

-0.06 0.18 0.06 -(/.22

0.32

-0.42

0.07

0.56

-0.63*

-0.09

0.22

-0.31"

0.07

0.57 0.54 0.87 0.85

-0.68* -0.69* -0.79 -0.81"

0.00 0.16 -0.42 -0.40

0.18

-0.26

0.07

0.54

-0.57*

-0.17

0.44

-0.47

-0.12

-0.16 -0.31 -0.14 -0.42

-0.04 0.19 0.02 0.12

0.40 0.31 0.22 0.67*

* Achieves the criterion correlation of 0.5 (P < 0.03). levels of mean cerebral glucose utilization accords with reports that cerebral blood flow (carrying metabolic fuel) decreases during SWS 62,77, and that both mean and local levels of cerebral glucose utilization decrease during SWS in the m o n k e y 36,a8. A n y link between R E M and cerebral metabolism is less clear. R E M and wakefulness show different relationships with cerebral metabolic rate (the correlations differ significantly). In contrast, SWS and R E M correlations are not different. Thus, the actual level of cerebral metabolism during R E M may be like that of SWS; lower than that of wakefulness. We strongly suspect that this will prove to be the case. However, we failed to observe a significant negative correlation between cerebral metabolism and REM. Thus, any relationship between R E M and cerebral metabolism is weak. This observation of a weak relationship may result from our limited ability to obtain high R E M values during the isotope incubation period, or from a real difference in metabolism linked to the two ma-

* Achieves the criterion correlation of 0.5 (P < 0.03). jor sleep states. More conclusive evidence awaits further studies. Whatever the relationship between the mean level of cerebral metabolism and the sleep states, there is a way in which R E M and SWS are fundamentally different. Most regional correlations with SWS are negative, while most correlations with R E M are positive. SWS is associated with relatively low levels of metabolism in many regions, and with relatively high metabolism in only one region (the hypothalamus). In contrast, R E M is associated with relatively high metabolism in a n u m b e r of regions. Markedly low metabolism is very rare during REM. Thus, feline sleep states are characterized by different patterns of relative metabolism, which generally replicate those seen in the rat 55. Metabolic state-dependency

in putative h y p n o g e n i c

sites

We limited our search for hypnogenic foci to regions traditionally associated with sleep generation. In these regions, a reasonable argument could be made that metabolic state-dependency reflects functional activity associated with hypnogenesis. However, none of the relevant pontine or basal forebrain regions exhibit even moderate state-dependency (Tables I and II). This negative finding fails to support the presence of localized hypnogenic regions in aminergic nuclei and in the basal forebrain. Perhaps hypno-

118

Fig. 2. Digitized autoradiographs (at normal contrast, no image processing) showing relatively high levels of metabolism (greater density) in the lateral geniculate (LG'N) and pulvinar (PUL) nuclei during wake (A) and SWS (B). Note that the medial geniculate (MGN) shows some focal points of high metabolism in the sleeping animal but is, in total, less active during SWS. This pattern is characteristic of thalamic regions, many of which exhibit higher-than-average metabolism (high density) during wakefulness but appear much like surrounding tissue during SWS.

genic regions are diffusely organized, and so are not easily delineated by our methods. The hypothalamus and some medial thalamic regions, which have been implicated in state-modulation, do exhibit metabolic state-dependency. This may reflect active hypnogenesis, but could also represent state-dependency in other thalamic and hypothalamic functions. Some of these functions, such as thermoregulation or feeding, are state-dependent.

Metabolic state-dependency and the reticular formation Classic reticular theory suggests that the arousal level of the brain is controlled by tonic activating influences ascending from the mesencephalic and pontine reticular formation 46. A major portion of reticular projections to the forebrain synapse in the medial and intralaminar thalamus7,17,50,59,61,63, including the central lateral and mediodorsal thalamic nuclei (which show low relative metabolism during SWS). In the context of reticular theory, low relative metabolism in the intralaminar nuclei may reflect the removal of reticular influences, tonically present during wakefulness and REM. The metabolic data converge with anatomical and electrophysiological findings to support this hypothesis, that thalamic state-dependency reflects reticular influences. Medial thalamic neurons (in particular, the central lateral and mediodorsal nuclei) receive monosynaptic excitation from the reticular formation. This monosynaptic excitation could influence state-dependency in thalamic discharge rate 73, excitability24 and metabolism. Because the pattern of metabolic state-dependency in layer IV of neocortex (high during wake, low during SWS, uncorrelated with REM) is similar to that in the intralaminar and specific thalamic nuclei, and because cells in cortical layer IV are driven primarily by afferents from thalamus32,35,41, cortical metabolic state-dependency may reflect the operation of a 'functional circuit'. That is, thalamic and cortical state-dependency may both reflect the actions of reticular influences modulating cortical functional activity via projections to the intralaminar and specific thalamic nuclei. Metabolic state-dependency in sensory systems SWS affects the pattern of spontaneous neuronal discharge in brain regions with and without primary sensory function 19-21,26,29,43,51,72,74,75. This effect may reflect changes in the level of incoming stimulation (e.g. when the eyes close), or the actions of some internal influence modulating neuronal discharge rate. The present data support the latter view. Our animals were exposed to white noise before and during the [14C]2-DG incubation period. Therefore, there was a contrast in the exposure of two sensory systems to external stimuli. The visual system received lower levels of stimulation as the eyes closed during sleep,

119

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Mean Cerebral Metabolism q mol/100 g./min.

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50

Fig. 3. Product-moment correlations between relative metabolic activity (y-axis, local metabolism/mean brain metabolism) and state values (x-axis, percent) in the medial geniculate (A-C), lateral geniculate (D-F). and pulvinar (G-I) nuclei during wake. SWS and REM. Correlations between mean cerebral metabolism and arousal state are shown in K-M. In general, SWS is associated with lower levels of relative metabolism in sensory regions and in the brain as a whole. REM is not. but the auditory system remained exposed to relatively high levels of stimulation (white noise). Under these contrasting conditions, the auditory and visual thalamic relays (medial and lateral geniculate nuclei, pulvinar nucleus) and layer IV in both auditory and visual cortex exhibit lower relative metabolism during SWS. Therefore, the level of functional activity in sensory regions does not depend primarily on stimulus input. This finding accords with a report that metabolic activity in the visual cortex and lateral geniculate of sleeping cats remains low, even if the eyes are open and visual stimuli are presented during SWS3L We failed to observe an association between REM and relative metabolism in the auditory and visual systems. A negative finding is of minimal value, but it does suggest a qualitative similarity in the response of both sensory systems to REM. That is, sensorily isolated (visual; eyes closed) and non-isolated (auditory) regions of the diencephalon and forebrain show a similar absence of state-dependency during REM,

just as both systems show low relative metabolism during SWS. During both REM and SWS, some influence other than sensory stimulation may modulate activity in sensory systems. Activity in ascending reticular pathways influences neuronal activity in sensory systems (see ref. 68 for review). Reticular stimulation lowers perceptual thresholds for both visual and auditory stimuli 22,49, and enhances spontaneous and evoked activity in cortex-~4.6< Single unit and evoked potential responses in visual structures are enhanced during reticular stimulation concomitant with photic or electrical stimulation of the visual system~6.67,6< Uptake of [14C]2-DG in the rat auditory system is greater during reticular stimulation concurrent with auditory stimulation, than during auditory stimulation alone 2& Such reports of reticular influences upon sensory function converge with the present data to suggest that arousal status of the sensory forebrain is set by an internal state-dependent influence arising from the reticular formation.

120

Metabolic state-dependency in motor systems The functional mapping technique is particularly sensitive to metabolic activity used for the maintenance of ionic homeostasis across the cell membrane 70. W e o b s e r v e d metabolic state d e p e n d e n c y in regions previously r e p o r t e d to exhibit alterations in m e m b r a n e polarization during sleep. M e m b r a n e hyperpolarization is present in the lateral geniculate during SWS, but not during REM28. This pattern of polarization s t a t e - d e p e n d e n c y corresponds to the pattern of metabolic s t a t e - d e p e n d e n c y in the geniculate (low relative metabolism during SWS but not during R E M ) . Therefore, some metabolic state-dependency in sensory systems m a y reflect alterations in m e m b r a n e polarization level. R E M is characterized by atonia, a c c o m p a n i e d by tonic hyperpolarization of a - and ~-spinal m o t o n e u rons10,n,23, 54. W e did not observe any metabolic reflection of hyperpolarization in the ventral portions of the spinal cord, where most reticulospinal projections synapse on m o t o n e u r o n s . Recall that, elsewhere (e.g. in lateral geniculate), our m e t h o d s appear sensitive to m e m b r a n e polarization levels. Perhaps our failure to observe metabolic state-dependency in the spinal cord reflects the limited resolution of the [14C]2-DG technique. W e sampled regional, rather than cellular metabolism. Spinal m o t o n e u r o n s are o u t n u m b e r e d by interneurons in the ratio of about 7:13. The interneurons could mask any metabolic link between R E M and functional activity in spinal motoneurons. A similar diffuse organization of reticular neurons could underlie our failure to ob-

Fig. 4. Digitized autoradiographs (normal contrast) showing metabolism in the granular layer of cerebellar cortex. A is taken from an animal exhibiting primarily active wakefulness. Metabolism in the cerebellar cortex is high (arrows), relative to the average level of brain metabolism. B is from an animal with almost pure SWS. Although the sleeping cerebellum appears a bit less active than during active wakefulness, there is no significant correlation between cerebellar metabolism and SWS. This would suggest that cerebellar metabolism responds to SWS as does the average level of brain metabolism. C is from an animal with an approximately equal mixture of SWS and REM (pure REM is not available). Cerebellar metabolism is noticeably lower in this high-REM condition than it is in the active awake condition. In sum, metabolism in cerebellar cortex is markedly high during active wakefulness, markedly low during REM and is not linked to SWS. The cerebellar cortex is the only brain region showing a moderately strong association with decreased metabolism during REM.

121 serve metabolic state-dependency in most reticular regions, even though brainstem ~4 and mesencephalic31 reticular neurons show tonic membrane hyperpolarization during REM. We note that many of the correlations in cat reticular regions approximated 0.4, well below our criterion, but similar to significant correlations previously reported in many reticular regions of the ratSL We speculate that weak correlations between reticular metabolism and REM are present, but are degraded by the diffuse organization of reticular regions. Trigeminal motoneurons show hyperpolarization and reduced excitability during REM 11,13.47. Also, the principle and motor trigeminal nuclei are unusual in that, unlikely most brainstem nuclei, they exhibit REM-specific metabolic state-dependency. The trigeminal nucleus sends fibers to supply the masticatory muscles 9. Our observation of trigeminal state-dependency may reflect functional activity linked to the characteristic inhibition of the masseteric reflex during REM 15, and to trigeminal participation in the inhibitory brainstem mechanism linked to the atonia of REM33,38,39,42~66.

The primary role of the cerebellum in motor and postural adjustments is reflected in metabolic statedependency during REM, but not SWS. The cerebellum is the only major brain region exhibiting markedly low metabolism during REM. REM-linked cerebellar metabolism probably reflects more than functional alterations associated with immobility. Quiet wakefulness and SWS are both associated with immobility, but there is no cerebellar metabolic state-dependency during these states. Rather, it appears that cerebellar metabolism is most closely linked to the extremes of activity; that is, the muscular activity of active wakefulness (r = 0.62, P < 0.003) and the atonia of REM (r = -0.63, P < 0.003). The red nucleus, a motor region showing REMspecific metabolic state-dependency in both the cat and rat 55, receives afferents from the cerebellum. Rubrospinal projections are involved in the excitation of ct-motoneurons and static y-motoneurons of flexor muscles, and run parallel to corticospinal projections with similar terminations and effects 9. Metabolic state-dependency in the red nucleus may, therefore, reflect functional activity linked to modulation of spinal motoneuron excitability during REM ato-

nia. More generally, our finding of REM-specific metabolic state-dependency in the red and trigeminal nuclei and in the cerebellum argues against localization of influences upon REM atonia to small areas of the hindbrain. Rather. the motor phenomena of REM may originate within a widespread neuronal network extending well beyond the pontine region.

Metabolic state-dependency in the hippocampus Our observation of REM-specific metabolic statedependency in the hippocampus, and in cortical regions linked to the hippocampus, may reflect functional activity linked to the generation of rhythmical slow activity (theta) during REM. Theta appears to originate from state-dependent postsynaptic potentials in the hippocampal trisynaptic chain, which in turn receives its primary excitatory input from entorhinal cortex ~. During REM. metabolic state-dependency appears in entorhinal cortex, and in the first two steps of the trisynaptic chain (dentate granule cells and the CA3 field). This pattern is wellmatched to hippocampal regions implicated in theta generation.

Implications for theories o[ sleep functions A primary function of sleep may be to conserve energy expenditure during a period of obligate inactivity 30. Our data support an energy conservation view of sleep function. They also indirectly support a restorative hypothesis. It has often been suggested (see refs. 1, 2, 64) that energy conservation during sleep would shift the anabolic-catabolic balance in brain tissue toward the anabolic pole, with resulting restoration of the body and brain. For example, high levels of tissue potential energy (such as would accumulate during energy conservation) have been shown to favor protein synthesis (see refs. 1 and 2 for reviews). Thus protein synthesis could be elevated after a period of sleep. Unfortunately, [14C]2-DG autoradiography cannot reveal the origins of links between sleep and regional metabolism. These links may reflect many processes, including those underlying neuronal discharge, graded potentials and synthesis activities. Therefore, we can only speculate as to the possible outcomes of energy conservation during SWS. In the context of a restorative sleep function, we suggest that the energy-consuming processes of protein syn-

122 thesis m a y be m a x i m a l w h e n c a t a b o l i c p r o c e s s e s are

c u r r e n c e of e n e r g y - u s i n g synthetic activity. W e are

low and b o t h available e n e r g y and m e t a b o l i c levels

e v a l u a t i n g this hypothesis.

are relatively high. T h e s e are the characteristics of R E M . A net increase in p o t e n t i a l e n e r g y d u r i n g S W S is f o l l o w e d by R E M , which is a s s o c i a t e d with sup-

ACKNOWLEDGEMENTS

p r e s s i o n of catabolic p r o c e s s e s such as shivering ther-

This w o r k was s u p p o r t e d by M e d i c a l R e s e a r c h

m o g e n e s i s and m e t a b o l i c h e a t p r o d u c t i o n 27,53. Fur-

C o u n c i l of C a n a d a G r a n t M A - 7 2 4 4 to B . J . F . , and by

ther, R E M m a y not be as strongly l i n k e d to l o w e r

a N a t u r a l Sciences and E n g i n e e r i n g R e s e a r c h C o u n -

levels of c e r e b r a l m e t a b o l i s m as is S W S . T h e distinct-

cil of C a n a d a P o s t d o c t o r a l F e l l o w s h i p to P . R .

ive m e t a b o l i c p a t t e r n of R E M c o u l d reflect the oc-

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