The human hypothalamus: comparative morphometry and photoperiodic influences

D.F. Swaab, M.A. Hofman, M. Mirmiran, R. Ravid and F.W. van Leeuwen (Eds.) Progress in Brain Research, Vol. 93 0 1992 Elsevier Science Publishers B.V. All rights reserved.

133

CHAPTER 10

The human hypothalamus: comparative morphometry and photoperiodic influences Michel A. Hofrnan and Dick F. Swaab Netherlands Institute f o r Brain Research, 1105 A Z Amsterdam, The Netherlands

Introduction The concept of the hypothalamus as a distinct neurological entity concerned with a variety of regulatory processes dates back to the end of the 19th century (for reviews, see Morgane and Panksepp, 1979). In 1893, on the basis of embryological work, the Swiss anatomist Wilhelm His (18631934) proposed a subdivision of the brain as a framework for an anatomical nomenclature of the central nervous system (His, 1893). The point of departure was the five brain-vesicles model described by Von Baer in 1828. His subdivided the second of these vesicles, the Zwischenhirn, or diencephalon, into three regions: epithalamus, thalamus and hypothalamus, which were arranged as longitudinal zones in superposition to one another. In 1895 this nomenclature was accepted by the Anatomische Gesellschaft and was incorporated in the Baseler Nomina Anatomica (His, 1895). Comparative anatomical investigations of this part of the brain in subsequent years, indeed, revealed a general plan of organization among vertebrates (Ariens-Kappers et al., 1936; Le Gros Clark, 1938; see also Simmons, 1988). Despite this basic pattern, which consists of a number of invariants and unchanging spatial relationships between the constituent parts, the morphology of the mammalian diencephalon shows variations in relative position, form and dimensions of nuclei from species to species. Grunthal (1950), when studying the com-

parative anatomy of the hypothalamus in mammals, even declared: “Kein Hypothalamus sieht wie die ander aus”. From what is known about hypothalamic functioning, this brain area may even be expected to show a somewhat varying configuration between individuals of the same species, as a result of external factors. These transformations of the original “Bauplan”, however, only concern the relative change in the geometry of the regional and nuclear subdivisions, while the fundamental topographical pattern of the hypothalamus is preserved (Keyser, 1979). Although the complex cellular arrangement and multitude of afferent and efferent projections have made analysis of hypothalamic organization difficult, the mammalian hypothalamus is generally subdivided into three regions in the anteroposterior direction: (1) chiasmatic (preoptic) region; (2) tuberal region; and (3) mammillary region (see Brockhaus, 1942; Simmons, 1988; Saper, 1990). Each of these regions, in turn, contains groups of nerve cells, many of which are nothing more than diffuse and ill-defined condensations of cells, while others are more circumscribed and consist of cells of rather characteristic types. There is no doubt, however, that within regions of the hypothalamus, describable areas and nuclei with distinctive structural and cytoarchitectonic characteristics exist as distinct entities (see Braak and Braak, this volume). The cytoarchitectural plan of the human hypoT thalamus has been quite well mapped out by now,

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although the exact terminology has often been controversial (Le Gros Clark, 1938; Simmons, 1988; Saper, 1990). One major reason for the differences in the nomenclature is that the cell groups in the human hypothalamus are rarely as well differentiated as in most other mammalian species. In recent years, however, more detailed studies of cellular arrangement employing immunohistochemical methods have outlined various cell groups with considerably more precision (Braak and Braak, 1987; Saper, 1990). This technique has also allowed the exploration of chemically defined neuronal systems in the human brain (Swaab et al., 1985, Mai et al., 1991; Braak and Braak, this volume). It is now possible to draw comparisons with other species that can shed light on the functional organization of the human hypothalamus. Before 1900 there were only vague intimations of the function of the brain surrounding the third ventricle and these were based primarily on various pathological and assorted clinical observations (for a review, see Morgane, 1979). Since then a large body of experimental evidence has been derived implicating that this region of the brain contains the control systems which are critically involved in many homeostatic and rheostatic (Mrosovsky, 1990) regulatory processes. Among these are electrolyte balance, food ingestion and energy metabolism, thermoregulation, reproduction, immune response, and various emotional-affective states in addition to vigilance mechanisms. It is clear that the hypothalamus not only regulates the homeostasis within the “milieu interieur” of the organism, but is also involved in modulating relationships between the individual and its external physical, psychological and social environment. Experimental studies, largely in rodents and primates, have made it clear that the hypothalamus performs these faculties by means of its control of three main types of output systems: endocrine, autonomic and behavioral. The executive authority relating to all these processes has repeatedly been centered in the hypothalamus - thus creating a kind of “subcortical phrenology”. Many of the more behaviorally oriented studies of the past 40 years, in particular,

have placed “the hypothalamus as reigning supreme unto itself and interpreted it as some sort of sovereign center of centers” (Morgane, 1979, p. 7). Most of these studies have, accordingly, failed to place the hypothalamus in its proper relation to the remainder of the nervous system and to develop broader integrative conceptions of hypothalamic organization and function. In this context it is important to point out that the hypothalamus is only one of a series of functional levels in the brain and that, whereas it influences more caudal levels of somatic and autonomic function, the hypothalamus itself is likewise under a direct influence from rostra1 levels of the nervous system, most notably the cerebral cortex (see Morgane, 1979; Palkovits and Zaborsky, 1979). Size and scaling of the hypothalamus As Le Gros Clark (1938) noted more than half a century ago, the human hypothalamus accounts for only 4 cm3, or 0.3% of the normal adult brain volume. It should be kept in mind, however, that the human hypothalamus is still twice the size of a rat brain. A really minuscule hypothalamus is found in the pygmy shrew, Sorex minutus, an insectivore which weighs only 5 g when fully grown, with a brain size of 0.10 cm3. This creature, which is active day or night and at all seasons, has a hypothalamus which measures not more than 0.003 cm3. Yet, despite its modest dimensions, this region contains the integrative systems critical for the animal’s basic life support. In insectivores the volume of the hypothalamus relative to brain volume varies between 2% and 3%, whereas in prosimians the ratio is somewhat lower and accounts for about 1.5%. In anthropoid primates, such as monkeys, chimpanzees and human beings, the ratio is generally a fraction of 1%. A graphic representation of the volume of the hypothalamus as a function of brain volume in insectivores and primates (Fig. 1) reveals the reason for the specific differences between these species. It appears that the volume of the hypothalamus in insectivores increases almost as the first power

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Brain volume ( cm3 ) Fig. 1. Volume of the hypothalamus as a function of brain volume in insectivores and primates. Logarithmic scale. The curve represents the second-degree polynomial equation describing the relationship between the two variables for insectivores and primates together (for details see text). The allometric equations for each individual (sub)order are given by: Znsectivoru: log y = 1.41 + 0.96 log x (r = 0.997; P < 0.001); Prosimii: log y = 1.23 + 0.89 logx (r = 0.990; P < 0.001);Anthropoidea: logy = 1.38 + 0.71 log x (r = 0.992; P < 0.001). Note that the slopes of the standard major axes in primates are different from isometry (geometric similarity).

where y is volume of the hypothalamus (mm3) and x is brain volume (cm3) (R2 = 0.993; n = 34 species). Allometric analysis of the volume of the hypothalamus as a function of body size, on the other hand, shows that the hypothalamus scales in a similar way for insectivores and primates, irrespective of size or evolutionary history (Fig. 2). So, here, the distinction between the orders is not a scaling disparity, as with brain size, but rather reflects a difference between regression constants, as a result of which the hypothalamus in anthropoid primates is larger than in insectivores of comparable body size. This means that if a shrew, such as the Sorex minutus, were scaled up as the 0.6 power to the size of man it would have a hypothalamus of only about 880 mm3. The actual volume of the human hypothalamus, however, is 3600 mm3 (Stephan et al., 1981), which is four times larger than would be predicted from the equation for insectivores. Taken together, these findings indicate that the hypothalamus in mammals, like the cerebral cortex (Hofman, 1985, 1988), is highly correlated with brain size, irrespective of the ecological strategy or evolutionary history of the species considered. 1o5

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prosimians and anthropoid primates the proportion of the hypothalamus relative to brain size decreases in species with larger brains. Consequently, most primates have a relatively small hypothalamus as compared with less encephalized mammals, such as insectivores and rodents. Although not enough data are available at present to consider the allometric relationship between the volume of the hypothalamus and brain volume in all major mammalian taxa, the available data suggest that the general relationship between both structures can be described by a second-degree polynomial equation. For insectivores and primates the relationship is expressed by: logy

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Fig. 2. Volume of the hypothalamus as a function of body weight in insectivores and primtites. Logarithmic scale. Notice the non-overlapping arrays of points representing various tax: onomic groups.

136

Moreover, the human hypothalamus has just the size we may expect of such a large-brained mammal, but it is considerably larger than would be predicted from its body size. A completely different picture emerges from a comparative study of the pineal gland, or epiphysis, a hormone-producing organ located in the midline roof of the third ventricle (McKinley and Oldfield, 1990), which receives photic information from the eye via cell groups in the preoptic region of the hypothalamus (see next section). Allometric analysis of this part of the brain indicates that in primates the pineal volume is basically a linear function of brain volume, but that in insectivores the pineal increases disproportionally with brain size (Fig. 3). In other words, the volumetric relationship between the pineal and the brain in mammals, in contrast to the hypothalamus, depends on the taxonomic group studied. The present analysis further 1o3

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Fig. 4. Volume of the pineal gland as a function of body weight in insectivores and primates. Logarithmic scale. Insectivoru: log y = -2.81 + 0.95 log x (r = 0.941; P < 0.001); and primales: logy = -2.66 + 0.94 log x (r = 0.950;P < 0.001). It should be noted that the pineal scales in a similar way in insectivores and primates and is a linear function of body weight.

reveals that the relative pineal volume of nocturnal species does not deviate from that of diurnal species. From the allometric analysis of the pineal-body size relationship (Fig. 4) it is clear that the pineal scales in a similar way in insectivores and primates and that the scaling factors in both cases do not significantly deviate from unity. In other words, the epiphysis in insectivores and primates, and presumably in many other mammalian orders as well, is a linear function of body weight. For insectivores and primates the general relationship is given by:

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Brain volume ( cm3 ) Fig. 3. Volume of the pineal gland as a function of brain volume in insectivores and primates. Logarithmic scde. Insectivora: log y = -0.695 + 1.51 log x ( r = 0.993; P < 0.001); and primatexlogy = -1.12 + l.O6logx(r = 0.967;P < 0.001). No significant distinction was found between prosimians and anthropoid primates. Notice the large pineal volume of Tarsius (T) relative to its brain size and the relatively small size of the pineal gland in Gorilla (G). The slope of the standard major axis in insectivores is significantly different from isometry (P < 0.01).

where y is volume of the epiphysis (mm3) and x is body weight (8) (R2 = 0.939; n = 32 species). As the epiphysis in mammals is an endocrine gland, it is logical to consider its interspecific growth being bound to the volume of circulating blood and thus to body weight (see also Legait et al., 1976). The finding that total blood volume is directly proportional to body mass (Prothero, 1980), together with the comparative investigations presented in this

137

essay, support the idea that, across species, the size and synthetic activity of the mammalian pineal varies directly with the animal’s size. However, variations in the morphology and functional activity of certain brain regions, such as the pineal and suprachiasmatic nucleus, may also occur among individuals belonging to the same species, under the influence of environmental stimuli, such as the natural light-dark cycle and seasonal variations in photoperiod. The preoptic region of the hypothalamus Sexually dimorphic nucleus In mammals the preoptic region of the hypothalamus is thought to be implicated in the neural control of endocrine functions (Kelley and Pfaff, 1978). Particularly the medial part of the preoptic area, a region of the hypothalamus which is bordered rostrally by the lamina terminalis and caudally by the posterior edge of theoptic chiasm, is criticallyinvolved in the regulation of sexually differentiated functions under the influence of gonadal steroids (see Anderson et al., 1986; Watson et al., 1986). Recent studies have attempted to identify sex differences in the structure of the preoptic-anterior region that may underlie these functional differences (see De Vries et al., 1984). In 1978, Gorski and his co-workers identified and described an intensely staining cell group within the preoptic area of the rat, the size of which showed a markedly sexual dimorphism (Gorski et al., 1978). This sexually dimorphic nucleus of the preoptic area (SDN-POA) is still the most conspicuous morphological sex difference in the mammalian brain. In mature rats, in which the SDN-POA is 3 - 8 times larger in males than in females, this difference has been shown to be independent of the steroidal environment. Instead, the SDN-POA seems to be profoundly influenced by androgens circulating perinatally (Jacobson et al., 1980; Bloch and Gorski, 1988). Although the SDN-POA has been studied most extensively in the rat (see also Anderson et al., 1985; Robinson et al., 1986), similar sexual differences have been documented in homologous structures in guinea

pigs (Hines et al., 1985; Byne and Bleier, 1987), ferrets (Tobet et al., 1986), gerbils (Commins and Yahr, 1984) and in man (Swaab and Fliers, 1985; Hofman and Swaab, 1989). The human SDN-POA, which corresponds to the intermediate nucleus as described by Braak and Braak (1987), can already be distinguished in the fetal brain around mid-pregnancy. In a developmental study we found that it is only after the age of about 4 years that the human SDN-POA differentiates according to sex, due to a dramatic cell loss in females (Swaab and Hofman, 1988). As a result, the size, shape and cellular morphology of the SDNPOA in adulthood exhibit a striking sexual dimorphism, as well as a sex-dependent pattern of aging (Swaab and Fliers, 1985; Hofman and Swaab, 1989; Swaab et al., this volume). Whereas numerous studies have implicated the medial preoptic area in the mediation and regulation of masculine sexual behavior and reproductive functions (Dohler et al., 1986; Byne and Bleier, 1987) it is not possible at this time to specify the precise role of the SDN-POA within this area. Considering its marked sexual dimorphism and its androgenic sensitivity during development, the SDNPOA might be part of the neural circuitry underlying masculine reproductive processes and scentmarking (Byne and Bleier, 1987; Turkenburg et al., 1988; De Jonge et al., 1990; Yahr and Finn, 1990). Suprachiasmatic nucleus In addition to its involvement in reproductive functions the preoptic region of the mammalian hypothalamus is also considered to be implicated in the temporal organization of biological rhythms (Rusak and Zucker, 1979; Moore-Ede et al., 1982; Meijer and Rietveld, 1989). The suprachiasmatic nucleus (SCN), a collection of parvocellular neurons, located in the basal part of the hypothalamus, just above the optic chiasm, is thought to be the principal component of this central clock mechanism. This bilateral cell group, first described by the Hungarian anatomist Lenhossek in 1887, is less impressive in humans than in many other mammalian species (Hofman et al., 1988) and may be dif-

138

Fig. 5 . Vasopressin-stained frontal sections (6pm) of the human hypothalamus. A. The SCN is situated just dorsal to the optic chiasm. The principal mass of VP-immunoreactive cells lies in the dorsal crescent of the SCN, from which strands of loosely packed cells descend on all sides, surrounding a central unlabeled area. Scale bar represents 0.2 mm. B. Higher magnification of the same section. Scale bar is 0.1 mm. OC, Optic chiasm; SCN, suprachiasmatic nucleus; 111, third ventricle.

ficult to recognize in Nissl-stained material (Saper, 1990). The homology of this cell group with the suprachiasmatic nucleus in rodents and non-human primates has only recently been partly established by application of immunohistochemical methods (Lydic et al., 1980; Stopa et al., 1984; Swaab et al., 1985; see also Fig. 5 ) . Morphometric studies have shown that there is no significant sexual dimorphism in the volume and cellular morphometry of the human SCN, with the exception of a difference in shape (Swaab et al., 1985; Hofman et al., 1988). The human SCN has been found to be elongated in females and more spherical in males. Such a sexual dimorphism in shape could conceivably have functional consequences by virtue of differences in contacts between the suprachiasmatic nucleus and structures in its vicinity. Other indications for the assumed func-

tional sex differences of the SCN come from studies in the rat, where it has been found that the volume of the SCN in males is larger than that in females (Gorski et al., 1978; Robinson et al., 1986). It is plausible, therefore, to assume that the SCN of male rats contains more nerve cells than the female SCN, which is relevant in view of the hypothetical relationship between cell number and the pacemaker properties of the SCN (Van den Pol and Powley, 1979; Pickard and Turek, 1985). On the other hand, the reduced size of the neuronal nucleoli in the SCN of male rats (Guldner, 1983) may point to a lower metabolic activity of male SCN neurons (Zambrano and De Robertis, 1968). As these properties may have a compensatory effect, the overall functional capacity of the SCN in male rats does not necessarily have to be different from that of female rats. Whether there is a differential sex effect on the

139

functional activity of the human SCN is not known but seems not very likely in view of the similarities in the SCN cellular morphology of men and women. On the other hand, the human SCN, being only 3.7 times larger than the SCN of the rat, is reduced in size relative to other hypothalamic nuclei, such as the paraventricular nucleus and supraoptic nucleus (Hofman et al., 1988, 1990). Whether this relative reduction in size and neuronal content of the human SCN is a consequence of a diminished significance of the SCN as the central biological clock in humans, in favor of other neuronal oscillators, or is merely an allometric scaling phenomenon, is not known. If, however, the disproportional reduction of the human SCN is due to allometry, it would mean that a relatively small population of neurons in this nucleus is already sufficient to generate and coordinate a wide spectrum of physiological and behavioral rhythms in mammals, irrespective of the size of the organism or its ecological strategy. The suprachiasmatic nucleus as neuronal clock The mammalian SCN is generally considered to be the major component of a biological clock, which generates and coordinates a wide spectrum of biochemical, physiological, endocrine and behavioral circadian rhythms (for reviews, see Rusak and Zucker, 1979; Turek, 1985; Meijer and Rietveld, 1989). The SCN receives photic information by a direct neural pathway from the retina, which exists in all mammals studied so far, including man (Sadun et al., 1984). This retinohypothalamic tract appears to be both necessary and sufficient for synchronization of the period and phase of circadian rhythms to the environmental light-dark cycle. Furthermore, indirect retinal projections have been found to enter the SCN via the ventral lateral geniculate nucleus and raphe nuclei (Moore et al., 1978; Harrington et al., 1987; Mikkelsen, 1990). Consistent with its role in the temporal organization of circadian processes, investigations in rodents and non-human primates suggest that the SCN is also involved in the seasonal control of reproductive and metabolic phenomena (for reviews, see Rusak

and Zucker, 1979; Follett and Follett, 1981; Gwinner, 1986). In recent years it has become clear that in mammals the pineal gland and the suprachiasmatic nucleus are essential for the regulation of these photoperiodic responses (see, e.g., Goldman and Darrow, 1983; Mess and Ruzsas, 1986; Cassone, 1990; Meijer, 1990). Interruption of the retino-hypothalamic pathway, or changes in environmental lighting conditions were found to influence the rhythm of the suprachiasmatic pacemaker, and consequently the synthesizing activity of the pineal gland. In mammals, the circadian synthesis and secretion of the hormone melatonin exhibited by the pineal gland is generated by oscillators in the SCN and is communicated to the pineal via a complex multisynaptic pathway (Moore, 1983; Tamarkin et al., 1985; Binkley, 1988; Krause and Dubocovich, 1990; see also Fig. 6). Disruption of any portion of this pathway from the SCN to the pineal gland abolishes melatonin rhythmicity. These findings strongly suggest that the endocrine

Fig. 6. Diagram of the human brain (mid-sagittal section) showing the neural pathways (dashed line) by which photoperiodic information reaches the pineal. Abbreviations: SCN, suprachiasmatic nucleus; PVN, paraventricular nucleus; SCG, superior cervical ganglion.

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activity of the mammalian pineal is under neural control, and receives a major input from the SCN. This means that in addition to its role as a circadian pacemaker, the SCN may also be involved in the seasonal timing of a number of physiological and behavioral processes by regulation of the photoperiod-dependent changes in melatonin secretion (Arendt and Broadway, 1987; Cassone, 1990). Seasonal variations in the human SCN Since the environmental light-dark cycle is the main "Zeitgeber" for circadian and seasonal rhythms in most species, including man, photic information could have substantial effects, not only on the neural activity of the suprachiasmatic nucleus but also on its underlying structure. Recently, we conducted a study to determine whether variations in light intensity, diurnal as well as seasonal, affect the morphology of the SCN in human beings (Hofman and Swaab, 1992). A marked seasonal variation was observed in the volume, total cell number and number of vasopressin cells of the human SCN (Table I). The volume of the SCN was, on average, twice as large in the autumn as in the summer and contained almost twice as many cells. Similar seasonal differences were found for the number of vasopressin-contain-

ing neurons. In general, the human SCN is smaller in the summer than in any other season. In contrast, no such seasonal variations could be detected in cell density or in mean cell-nuclear diameter. The sexually dimorphic nucleus of the preoptic area (SDN-POA), located in the immediate vicinity of the SCN, did not show any significant periodic changes over the year in either volume or cell number. Differentiation of the data by gender did not affect the outcomes: no significant seasonal variations in the SDN-POA could be detected for either sex (Fig. 7). In contrast with the annual cycle of the human SCN, no significant diurnal variations in either volume or cell number were observed. The SDNPOA, like the SCN, did not show diurnal variations, irrespective of whether sexes were pooled or analyzed separately. Moreover, no diurnal changes could be detected in cell density or in mean cell-nuclear diameter in either the SCN or the SDN-POA, except for the mean diameter of cell nuclei in the SDN-POA of male subjects, which was significantly larger during the daytime (06.00 - 18.00 h) than during the nighttime (18.00-06.00 h), suggesting a diurnal variation in cell activity in this hypothalamic nucleus in males under the influence of light. Taken together, these results indicate that the morphology of the human SCN is significantly affected by

TABLE I Seasonal variations in the volume, total cell number and vasopressin cell number of the human suprachiasmatic nucleus Season

Winter Spring Summer Autumn

No. of subjects

Period

306"-35" midpoint: 21 December 36" - 125' midpoint: 23 March 126" -215" midpoint: 22 June 216" - 305" midpoint: 21 September

' Values are given as mean

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S.E.M.

Suprachiasmatic nucleus' Volume (mm3)

Total cell number ( x I d )

Vasopressin cell number ( x lo3)

17

0.240 k 0.025

48.67 k 3.90

7.00 f 0.75

9

0.278 f 0.031

46.30 f 4.05

7.41 f 0.89

11

0.174 f 0.019

30.28 f 4.19

4.45 f 0.70

11

0.344 f 0.050

58.35 k 5.82

9.95 k 1.38

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Fig. 7. Seasonal variations in the volume and total cell number of the suprachiasmatic nucleus (SCN) and sexually dimorphic nucleus of the preoptic area (SDN-POA) in human subjects, differentiated by gender. Subjects were grouped into four annual periods of equal length based on the time of death (see Table I). Data are expressed as deviations from the annual mean. In general, the human SCN shows a marked seasonai variation with low values in the summer and higher values in other seasons. The observed seasona1fluctuations in the morphology of the SDN-POA are less prominent, and statistically not significant ( P > 0.6).

seasonal variations in photoperiod, but not by the daily light-dark cycle. Although human beings are not considered to be particularly photoperiodic, many of the annual rhythms of human biology are under environmental control, and seem to be driven by an endogenous clock synchronized with the seasons. Several investigations indicate that the SCN and its vasopressin transmitter system are part of the neural substrate that mediates these circannual rhythms (for reviews, see Follett and Follett, 1981; Mess and Rdzsas, 1986; Hermes, 1991). The striking seasonal variation in the total volume and vasopressin cell number of the human SCN is in accordance with this view. The morphology of other parts of the brain that are thought to be critical for the generation of annual cycles, such as the pineal gland, have also been found to undergo seasonal variations. Investigations in rodents showed that both the pineal vo-

lume and nuclear size of pinealocytes are considerably larger in winter than during the summer period, while the number of “synaptic” ribbons in the pineal, associated with the cyclic biosynthesis of melatonin, have also been found to undergo seasonal variations (Peschke et al., 1989; McNulty et al., 1990). Whether there are cyclic variations in the morphology of the human pineal has not been investigated so far. Since the SCN innervation of the paraventricular nucleus (PVN) of the hypothalamus represents the primary, if not the sole, pathway by which photoperiodic information is relayed to the pineal (Pickard and Turek, 1985; Tamarkin et al., 1985; Smale et al., 1989) the neural connections between the SCN and the PVN seem critical for the generation of seasonal cycles. Therefore, we looked for seasonal changes in the structure of the PVN as we observed in the SCN. A preliminary study conduct-

142

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Fig. 8. Seasonal variations in the volume of three vasopressincontaining cell groups in the human hypothalamus: SCN, suprachiasmatic nucleus; PVN, paraventricular nucleus; SON, supraoptic nucleus. Significant changes were observed in the volume of the SCN ( - 33%, P < 0.01) during the summer, and in the volume of the PVN ( + 41070, P < 0.02) during the spring. For further details see legend to Fig. 7 .

ed on the human PVN in relation to photoperiod indeed showed a notable seasonal variation in the total volume of the PVN (Fig. 8). The human PVN, however, seems to reach its peak during the spring, whereas the SCN has its maximum size in early autumn. Several brain regions, on the other hand, which are not known to be involved in the temporal organization of biological processes, such as the supraoptic nucleus, do not show significant annual oscillations (Fig. 8). This means that not every cell group in the human hypothalamus is subject to seasonal changes, but probably only those regions which are directly involved in the transmission of photoperiodic information.

form of the SCN annual cycle shows two maxima with a time interval of about 6 months: one peak, with a low amplitude, close to the spring equinox, and a second, more prominent peak, near the vernal equinox, moments of the year when the length of daylight is equal to the length of darkness. Furthermore, the annual minimum was found to coincide with the summer solstice; i.e., the longest photoperiod, whereas a second minimum was observed near the winter solstice. These findings indicate that the bimodal SCN curve reaches its positive amplitude at the same moment when the photoperiod undergoes its largest rate of change (Fig. 10). Sho tening days in autumn, as well as lengthening days early spring, seem to induce morphological changes in the human SCN. These findings indicate that photoperiod may be considered as a potential environmental factor controlling the size of the SCN, and that photoperiodic change rather than day length itself is the essential parameter governing this process. If photoperiod is the effective seasonal Zeitgeber in man, as it is in many vertebrate species (see, e.g., Gwinner, 1986), existence of human beings near the equator, where major seasonal variations in day length do not occur, may, therefore, lead to a desynchronization of the underlying

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At higher latitudes, as in the Netherlands, where changes in day length are pronounced, light-dark information is the main Zeitgeber for the endogenous annual timing system. To investigate the assumed phase relationship between the annual variations in the SCN, the dynamic changes in photoperiod variations in SCN cell number over the year have been correlated with the natural photoperiodic conditions at 52" Northern latitude (Fig. 9). The wave

MAR

JUN

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Time of

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1

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Fig. 9. Annual variations in total cell number of the human suprachiasmatic nucleus (SCN) in relation to the photoperiodic cycle of the temperate zone (52" N). In these double-plotted histograms the SCN data are grouped into 1.5 month periods and expressed as deviations from the annual mean, whereas the photoperiodic deviations from the annual mean are given as a cosine curve. Notice the bimodal wave form of the SCN curve with one maximum close to the spring equinox (March) and the other near the vernal equinox (September - October).

143 SUPRACHIASMATIC NUCLEUS

I # # ,, 1 1 1 1 1 1 1 1 , 1 1 , , 1 , 1 1 1 , 1 MAR

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DEC

MAR

JUN

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OEC

Time of year (months)

Fig. 10. Schematic representation of the latitude-specific influence of photoperiod on the cell number of the human suprachiasmatic nucleus (SCN). The best correlation (Spearman’s e = 0.732, P < 0.05) between the two variables was achieved by correlating the deviations of the total number from the annual mean (upper curve) with the first derivative of the photoperiodic cycle (lower curve). Note that large cell numbers in the SCN coincide with the moment that the photoperiod undergoes its largest rate of change and vice versa.

periodic processes and, consequently, to a subduction of the amplitudes of the SCN cycle. The complexity of the seasonal variations in the SCN, however, suggests that, in addition to the environmental lighting conditions, other non-photic signals are involved in generating this phenomenon. There is now substantial evidence that the SCN and pineal gland are involved in a neuroendocrine “feedback loop’’ (for reviews, see Mess and RUzsAs, 1986; Rosenwasser and Adler, 1986; Cassone, 1990). In mammals, pineal synthesis and secretion of melatonin and possibly other hormonal products follow a diurnal and seasonal rhythm that is imposed on the pineal by the SCN via a hypothalamo-pineal pathway (Fig. 6). Melatonin synthesis shows maximum values during the subjective night in both diurnal and nocturnal species (Klein, 1979; Skene et al., 1990) and the pattern is further influenced by photoperiod (Glass, 1984; VanEEek and Illnerova, 1985; Underwood and Goldman, 1987). On long photoperiods, as in summer, the period of high melatonin synthesis is short, while on short periods, as in winter, it is prolonged. Conversely, the SCN may be an important central target mediating the

physiological effects of circulating melatonin (VanEEek et al., 1987; Reppert et al., 1988). Gonadal hormones probably also mediate the period, phase and coherence of activity rhythms which occur in association with natural reproductive cycles including estrous cycles and photoperiodic responses (Morin and Cummings, 1981; Gwinner, 1986; Rosenwasser and Adler, 1986). Steroid effects on circadian rhythms have been observed in both birds and mammals, which has led several authors to suggest that gonadal secretions may play a role in oscillator coupling in the vertebrate timekeeping system (Rosenwasser and Adler, 1986). Normally, the timing of gonadal steroid hormone secretion is controlled by pituitary gonadotrophins, which are themselves strongly influenced by the SCN (Samson and McCann, 1979; Kawakami et al., 1980). Thus a neuroendocrine feedback loop involving SCN-pituitary-gonadal interactions is a distinct possibility. This hypothesis is further supported by observations that gonadal hormones can influence SCN electrophysiological and neurochemical processes (Kow and Pfaff, 1984; Miller et al., 1984). Taken together, these findings support the hypothesis that the suprachiasmatic nucleus, pineal gland and gonads are critically involved in the generation and control of various circadian and circannual rhythms in mammals. Finally, the present findings indicate that photoperiod is a putative environmental factor controlling the size and functional activity of the human SCN. Therefore, disturbances of the annual cycle of vasopressin synthesis in the SCN may have profound effects on the seasonal timing of a variety of physiological and behavioral processes. It might explain, for example, why light therapy of patients with seasonal affective disorders, a syndrome characterized by regularly recurring depressions in autumdwinter, shows such a spectacular remission of symptoms after a few days of treatment with bright light (Lewy et al., 1982; Arendt and Broadway, 1987; Rosenthal et al., 1988). Although melatonin has been invoked as the critical biochemical mediator of the light-dependent effects in such mood disturbances it does not seem to be implicated

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in this process (Wehr et al., 1986). In view of the assumed seasonal variations in vasopressin synthesis in the human SCN it would be worthwhile to investigate whether the anti-depressant effect of phototherapy is due to an activation of the vasopressin system - or any of the other immunocytochemically defined neuronal clusters - of this hypothalamic nucleus. Summary and conclusions The concept of the hypothalamus as a distinct neurological entity concerned with a variety of regulatory processes dates back to the end of the 19th century. Before 1900 there were only vague intimations of the function of the brain surrounding the third ventricle and these were based primarily on various pathological and assorted clinical observations. Since then a large body of evidence has been derived implicating that the hypothalamus contains the control systems which are critically involved in many physiological, endocrine and behavioral processes. Among these are feeding and drinking, reproduction and the regulation of the sleep-wake cycle and temperature. Although the human hypothalamus accounts for only 4 cm3, or 0.3% of the adult brain volume, it contains the integrative systems critical for all these processes. A comparative morphometric analysis of the hypothalamus among mammals revealed that the volume of this part of the brain is highly correlated with brain size, irrespective of the ecological strategy or evolutionary history of the species considered. It appears that the human hypothalamus has just the size we may expect of such a largebrained mammal, but it is considerably larger than would be predicted from its body size. In mammals the preoptic region of the hypothalamus is implicated in the neural control of endocrine functions and in the temporal organization of a wide spectrum of biological rhythms. In recent years, the pivotal role of two hypothalamic cell groups have been considered in this context: the sexually dimorphic nucleus (SDN-POA) as part of the neural circuitry underlying masculine sexual behavior and

reproductive functions and the suprachiasmatic nucleus (SCN) as the principal component of the central clock mechanism. Consistent with its role in the temporal organization of circadian processes, investigations in rodents and non-human primates suggest that the SCN is also involved in the seasonal control of reproductive and metabolic phenomena. Since the environmental light-dark cycle is the main Zeitgeber for circadian and seasonal rhythms in most species, including man, photic information could have substantial effects, not only on the neural activity of the biological clock, but also on its underlying structure. Our observations on the human SCN in relation to photoperiod indeed revealed a marked seasonal variation in the morphology of the human SCN. The volume of the SCN was, on average, twice as large in the autumn as in the summer and contained more than twice as many vasopressin immunoreactive neurons. In general the human SCN is smaller in the summer than in any other season. In contrast, no such seasonal variations could be detected in cell density or in mean cellnuclear diameter. The SDN-POA did not show any significant periodic changes over the year in either volume or cell number, indicating the specificity of the SCN oscillations. In contrast with the annual cycle of the SCN, no significant diurnal variations were observed in any of the morphological parameters considered in either the SCN or SDN-POA. Taken together, these results indicate that the human SCN, in contrast with the SDN-POA, is significantly affected by seasonal variations in photoperiod, whereas the daily light-dark cycle per se does not seem to induce comparable modulations in either nucleus. The complexity of the annual SCN cycle, however, suggests that, in addition to the environmental lighting conditions, other non-photic signals (e.g., gonadal hormones) are involved in generating this phenomenon. Acknowledgements The authors are indebted to Mr. B. Fisser for his technical assistance, Mr. H. Stoffels for drawing the

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figures and Ms. W. Verweij for her secretarial help. Brain material was obtained from the Netherlands Brain Bank (coordinator Dr. R. Ravid).

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Discussion R.Y. Moore: First, how do you determine total cell number in the suprachiasmatic nucleus? Second, how do you account for seasonal changes in total cell number as it seems unlikely that new neurons are being formed? Could this be a function of the season of death rather than a seasonal rhythm? M.A. Hofman: In our study the SCN was defined according to immunocytochemical criteria by using vasopressin as a marker. The number of vasopressin neurons was first counted in this material. Subsequently, the total number of cells (i.e., neurons and glial cells) in this subdivision of the SCN was estimated by counting the profile density per unit area in thionin-stained material (Swaab et al., 1985). I agree that the more than two-fold difference in the number of vasopressin-immunoreactive neurons of the human SCN between late spring and early autumn raises a number of questions about the underlying mechanism. It could be that changes in photoperiod influence the rate of vasopressin synthesis of the SCN and that groups of peptidergic neurons are activated during particular periods of the year, depending on day length, light intensity or other photic parameters. Another, more speculative, explanation for the seasonal variations in SCN morphology is that the volumetric changes reflect the periodic production and/or incorporation of new neurons. Further experimental studies should be performed in non-human mammals to examine the exact nature of the seasonally dependent neural plasticity of the biological clock. H.B.M. Uylings: You showed a clear seasonal variation in the number of visibly stained vasopressin (VP) neurons in the SCN: but, in addition to the comments of Dr. Moore concerning the volume of the SCN and its total cell number, do you agree that other criteria than VP, for example, neurotensin, may be crucial for the determination of the volume of the SCN. M.A. Hofman: Since the cytoarchitectural boundaries of the SCN are difficult to delineate in conventionally stained sections it is indeed important that, in addition to vasopressin, other neuropeptides, such as neurotensin or vasoactive intestinal polypeptide, should be used as neuronal markers. It will provide more insight in the dimensions of the human SCN. H.P.H. Kremer: (1) A similar phenomenon of seasonal variations is described for the projection neurons of the song control system of oscine songbirds. (2) Could you comment upon the exact way of counting the neurons? M.A. Hofman: It is correct that in some avian brains, especially in the high vocal center (HVC) of the neostriatum in canaries and zebrafinches, new neurons continue to be added in adult life (Nottebohm et al., 1986;Alvarez-Buylla et al., 1990). In adult male canaries, for example, new HVC neurons are born in the month of September, and survive for at least 8 months (Kim et al., 1991).The longevity of the HVC neurons suggests that these cells remain part of the vocal control circuit long enough to participate in the yearly renewal of the song repertoire. Whether

such an oscillating pattern of neurogenesis occurs in the mammalian SCN remains to be seen. As to your other question, the number of vasopressin neurons in the SCN of each subject was estimated by counting the number of nuclear profiles per unit area followed by a discrete unfolding procedure and a correction for section thickness (Swaab et al., 1985). J.K. Mai: The glial cells within the human SCN have contact with the organum vasculosum of the lamina terminalis, the ependymal lining, pial surface and blood vessels. It could therefore well be that glial cells of the SCN change their volume (e.g., during different seasons) thereby ensuing technical problems in distinguishing neurons and glial cells. My question is: taken into account this possible effect how did soma size and cross-sectional areas of both cell populations overlap? M.A. Hofman: Differentiation between neurons and glial cells has not been made in the morphometric analysis, except for the group of vasopressin-expressing neurons. Your suggestion, though, that changes in the soma size of glial cells might explain the seasonal variations in the volume of the human SCN seems not very likely, since volume changes in glial cells due to osmotic, potassium, or transmitter induced gradients (Walz, 1989)are far too small to account for the 150% difference in SCN volume between May - June and October - November. Moreover, periodic oscillations in the volume of glial cells would affect the numerical cell density of the SCN over the year, which has not been found (Hofman and Swaab, 1992). W.A. Scherbaum: Do you know if there exist osmoreceptor in. puts to the SCN, and if there exist projections to the PVN: e.g. to vasopressin cells or the CRH cells which might explain pe. riodicity in drinking behavior and control rhythmicity? M.A. Hofman: No osmoreceptor inputs to the SCN have beer described, at least not to my knowledge. R. Ravid: Can you dissociate the effect of light from the effeci of temperature on variations in the SCN? M.A. Hofman: It is not easy to differentiate between the specific influences of these environmental factors upon the morphologj of the human hypothalamic clock, but when the subjects werc grouped into four annual periods based on a thermic division 01 theyear instead of on a photoperiodic division, no significant an nual fluctuations in the volume or cell number of the SCN werc observed. These findings suggest that the human SCN is highl! affected by seasonal variations in photoperiod, but not b! changes in temperature.

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