Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
A Brain Adaptation View of Plasticity: Is Synaptic Plasticity An Overly Limited Concept? AUTHOR LIST 1Beckman Institute, 2Neuroscience Program, 3Medical Scholars Program, 4Departments of Psychology, 5Psychiatry, and Cell and Structural Biology, University of Illinois at Urbana-Champaign Address correspondence and reprint requests to: William T. Greenough, Ph.D. Beckman Institute 405 N. Mathews University of Illinois at Urbana-Champaign Urbana, IL 61801 Phone: 217-333-4472 Fax: 217-244-5180 Email: [email protected] 1 Abstract There is a long tradition, traceable to the early musings of Ramon y Cajal, of focusing on the neuron as the only plastic cell type of any importance within the brain, and on the synapse as the only important plastic aspect regulating the interactions between neurons. While neuronal and synaptic plasticity are without question important aspects of brain function, it has become increasingly clear that other cellular elements of brain are plastic and that their plasticity can contribute to brain function. For example, oligodendrocytes, astrocytes, vasculature, and perhaps other neuropil components also exhibit plasticity in the developing and mature brain. The different components of an experience appear to influence each of these cellular elements differently. It is also becoming clear that these various forms of brain plasticity likely have distinct functional purposes. Exposure to a complex environment, for example, causes synaptogenesis in animals genetically rendered incapable of the most common form of long-term potentiation, suggesting that these forms of plasticity serve different purposes in the brain. In short, while research focuses largely on naturally- and artificiallyinduced changes in synaptic connectivity, the brains of animals (and presumably people) in real-world situations are in a dynamic state in which synaptic adjustment may in some cases be a relatively small part of the mix. Here we review some of the data that suggest the existence of multiple forms of plasticity, and briefly discuss how these changes might differentially affect functional brain organization. 2 Roots of neuronal plasticity Since the early speculations of Tanzi and Ramon y Cajal, the synapse has been the principal proposed site of plasticity underlying learning and memory in the brain. Tanzi (1893) initially emphasized the possibility of strength changes in pre-existing connections while Ramon y Cajal (1893) stressed the formation and loss of connections. The ability to examine these possibilities was limited by the availability of adequate tools, but, by the early 1970s, electrophysiological and anatomical evidence of the nervous system’s ability to alter its functional connectivity in accord with its experience was becoming reasonably well established. Electrophysiologically, activity-dependent modification of postsynaptic responses were described in invertebrates (Castellucci, 1978 #200), and in the mammalian visual system (Hubel, 1977 #196), and long-term potentiation was proposed as a vertebrate model of neural learning (Bliss and Lomo, 1973). Anatomically, there was evidence that synapses in the late developing and adult nervous system could both form and change in size in response to experience; functional innervation of neurons by surviving axons occurred spontaneously in response to denervation (e.g. Lynch et al., 1973; Raisman and Field, 1973); CAN WE TALK HERE ABOUT NON-EC EVIDENCE FOR ADULT PLASTICITY HERE? – possibly use anatomical observations from associative learning paradigms I think this might better go in later below Here we summarize progress in understanding the various types of brain plasticity thought to be associated with learning and memory, focusing heavily on our own work, since those relatively early beginnings. 3 Contributions of Complex Environment Research to Plasticity The complex environment housing paradigm, pioneered by Hebb (1949) and his students (e.g., Hymovitch, 1952 #178), was first used as a tool for exploring brain plasticity by Krech, Rosenzweig, Bennett and colleagues (Bennett et al., 1964), who reported some of the earliest evidence for morphological brain plasticity in response to experience. It was subsequently reported that dendritic field dimensions (Volkmar and Greenough, 1972) and synaptic size (West and Greenough, 1972) were increased in the visual cortex of rats exposed to a complex environment (EC) from weaning through adolescence. A later report by Turner and Greenough (1985) demonstrated specifically that there were more synapses per neuron in upper layers of the visual cortex in rats reared in a complex environment. These observations demonstrated that behavioral experiences could be used as a tool to study very specific, measurable aspects of neuronal plasticity. It should be noted that there is a reason that we use the term “complex environment” instead of the oft-used term “enriched environment.” These laboratory environments are simply not enriched relative to the norm of wild or feral rats. We would argue that no one has published studies of the brains of rats that have been provided levels of environmental complexity and challenge beyond the level provided by the natural environment, and studies of wild animals have for years confirmed that feral animal brains are larger than those of domestically reared comparable animals (old german and other literature). 4 Nonetheless, studying different degrees of environmental complexity can provide information about brain responses that are likely to generalize to higher levels of stimulation, as suggested also by studies of the differential effects of environment on human development (e.g., Hart and Risley, 1995). Complex environment effects on neurons are widespread in brain In addition to the effects of complex environment on the visual cortex, neuronal responsiveness to activity and experience has been demonstrated in a wide variety of brain structures including hippocampus (Moser et al., 1994), basal ganglia (Comery et al., 1995; Comery et al., 1996), cerebellar cortex (Greenough et al., 1986), auditory cortex (Greenough [volkmar & Juraska, 1973]) and somatosensory cortex (Coq, 1998 #53) .**.{I think this is sufficient} At this point, neuronal plasticity seems to be the rule rather than the exception in CNS structures, although there are some striking failures to demonstrate it in some cases (Kleim et al., 1998; but see Jeff's new paper) – this is the LCN no-change paper) Kleim now has data showing dentate/interpositus?? plasticity in eyeblink conditioning. this should go in a separate section that Jeff will write. (I’m keeping these notes here until we’ve got this written….) Jeff can add more here or elsewhere see changed version, not done, on bill’s revision given to aaron Note that these lists are exemplary and not all-inclusive. 5 brief review of Neuronal forms of brain plasticity (basically set up all the measures of plasticity that we’ll be referring to later in the chapter) each topic should be described in light of all non-dichotomised forms of plasticity in which it has been observed (development, EC, lesion, monocular deprivation) Plasticity of synapse number Dendritic arborization has long been used as an indirect indicator of synapse number (or of available postsynaptic space). The magnitude of experience effects upon dendritic branching of representative visual cortex neuron types and upon the number of synapses per neuron was in the same range, a 20-25% increase in EC vs IC rats (Greenough and Volkmar, 1973 vs Turner and Greenough, 1985). Spine density was somewhat elevated on some EC visual cortex neurons as well (Globus et al., 1973?), and in caudate nucleus (Comery et al., 1995). Robust dendritic branching increases also occurred in rats placed in EC (vs IC) housing as adults (Greenough, Juraska and Volkmar, 1979) and in middle age (Green et al., 1983). The effects of a complex environment on dendritic branching appear largely to remain present through a subsequent period of exposure to IC housing (Camel et al., 1986). As noted above, exposure of rats to a complex environment increases the number of synapses per neuron in visual cortex. This is also seen in adults and, like dendritic effects, the synaptic effects largely survive a subsequent period of IC housing (Briones). Synaptic effects of EC exposure also occur in hippocampus (Tsien paper cited elsewhere). I don’t know what else should go in the preceding paragraph but it seems rather short might measures of the effects of learning on functional brain organization already be affected by these nonsynaptic changes?? What is this? A number of morphological effects have typically been viewed as odifications of pre:existing synapses, although they could reflect formation and/or loss of synapses with different properties. The simplest of these are measures of synaptic size (or the size of components such as the postsynaptic density (PSD) length, vesicle aggregates and the pre and postsynaptic processes themselves (e.g. West and Greenough, 1972; Sirevaag and Greenough, 1985). ***Not sure if anything else is needed here*** 6 Perforations : The curious discontinuities in the postsynaptic density characteristic of “perforated” synapses have been regularly associated with plastic synaptic change since they were first reported to increase with age and with complexity of experience in rat visual cortex (Greenough et al., 1978; see also Jones and Calverley, 1991). Geinisman and others reported that some types of these synapses increased in number following induction of LTP or kindling (e.g., Geinisman et al., 1991; Geinisman et al., 1990) and suggested that they might represent stages in a single synapse “splitting” into dual separate, innervated spines, the presence of multiple headed spines and their increases in number in both electrical and behavioral plasticity paradigms (Geinisman, 1989 #138; (Comery et al., 1996). Perforated synapses also increase after motor skill training (e.g., Kleim et al., in preparation; Jones et al., 1999). Fiala et al. (Fiala et al., 2002) argue that this is highly unlikely as mature axons pass through the gap between two spines connected to the same presynaptic process. However, this conclusion would appear to require a specific type of splitting in which the spine continuously maintained contact with both spines throughout the splitting process. If splitting involved transient retraction followed by re-extension to contact the presynaptic process (excluded from the definition of splitting by Fiala et al., 2002), it would be possible, even likely, that other processes would be contained between the daughter spines. Other forms of synaptic remodeling have also been proposed with regard to perforated synapse structures (e.g., Toni et al., 1999), and it is clear that the final words have yet to be written regarding this phenomenon. 7 MSBs Geinisman et al., (2001) reported MSBs in hippocampal subfield CA1 following associative eyeblink conditioning using the trace paradigm which requires an intact hippocampus in order to be learned. In general, according to (Kristen Harris), spines on a single hippocampal axonal varicosity sometimes arise from the same postsynaptic cell, but may also arise from distant processes or separate neurons. (**need to check this**) While there is debate about the processes whereby terminal boutons or en passant varicosities become contacted by more than one postsynaptic process, there are consistent reports that the frequency of such synapses is increased in behavioral and electrical plasticity paradigms. The implications of this finding for wiring diagram level models of the learning process remain to be determined. It should be noted that this phenomenon is not unique to the hippocampus—we have seen multiple postsynaptic contacts increased on excitatory morphology presynaptic varicosities in the visual cortex of rats reared in complex environments in comparison to caged rats (Jones et al., 1997). Moreover, Federmeier {in the earlier today version I cited Harris / Stevens cerebellum paper. That one had something like 70% of PC spines onto Pf varicosities coming from the same Purkinje cell. That still is relevant to the Federmeier et al paper (submitted) which found a dramatic increase in cerebellar msbs with acrobatic training. 8 TA Jones et al have also described increases in these multiple synapses in the intact cortex in the course of compensatory changes following unilateral cortical lesions, and a relatively early report indicated increased multiple postsynaptic innervation of presynaptic terminals associated with the open eye in monocularly-deprived (kittens?) (M. Friedlander). Persistence of neuronal changes TESS’s EC REVERSAL EFFECT ON SYNAPSE/NEURON, among others And jeff’s stuff NON-NEURONAL CHANGES The complex environment paradigm has been used extensively to examine the range of plasticity of non-neural elements, as well as neurons and synapses, but these data have largely failed to become incorporated into theoretical development regarding brain plasticity. Early in this history, for example, Diamond et al. (1966) reported that exposure to a complex environment induced changes in the number of glial cells in cerebral cortex. We have subsequently examined plasticity in glia and other non-neuronal elements of the cerebral cortex in response to complex environment exposure and find that, in general, these changes parallel those observed in neuronal dendrites and synapses. These observations suggest that all types of brain tissue may exhibit plasticity, at least in regions such as the cerebral and cerebellar cortices where this has been examined. 9 Astrocytes and the Complex Environment Following early reports on experience-induced plasticity of astrocytes (Diamond et al. 1966; Szeligo, 1977 #117), Sirevaag and Greenough (1991) found that the extent of GFAP-immunoreactive astrocytic processes was greater in EC than in IC rats This effect These effects of complexity that occur in brain areas that exhibit synaptic plasticity are differentiable from increases in astrocytic processes that result from stress seen, e.g., in the hippocampal formation (Sirevaag et al., 1991) and, at least in cerebellar cortex, the volume fraction of astrocytes parallels plasticity of synapse number on an individual animal basis (Anderson et al., 1994; see also Sirevaag and Greenough, 1988). THIS SECTION SHOULD GO IN THE DISSOCIATION OF PLASTICITY EFFECTS ON GLIA. The source of such inhibition likely stems from extragranular layers of cortex as rapid (physiologically-defined) changes in both visual (Trachtenberg, 2000 #188; Trachtenberg, 2001 #189) and somatosensory cortices (Diamond, 1994 #190) have been reported to occur prior to the expression of modifications in layer IV. Finally, observations by Gilbert and colleagues (Gilbert, 1979 #191; Gilbert, 1992 #192) further suggest that horizontal connections may be the source of such changes in visuo- and topographic-maps. 10 At a higher level of resolution, astrocytic process proliferation is more specifically associated with synapses, which are more completely ensheathed by astrocytic processes in EC rats (Jones and Greenough, 1996), presumably reflecting the function of optimizing the synaptic microenvironment. There are substantial reasons to expect astrtocytic plasticity to have functional consequences. Glia influence synaptic function in ways that range from efficacy modulation (e.g., Araque et al., 1998; Smit et al., 2001) to the apparent dissection of presynaptic from postsynaptic processes in synaptic remodeling (e.g., Hatton, 1997; Meshul et al., 1987; Salm, 2000). Astrocytes can conduct excitation via propagated Ca2+ waves (e.g., Araque et al., 1999; Dani et al., 1992) which interact with neuronal activity (e.g., Rouach et al., 2000). Glial cells take up and metabolize glutamate and GABA (e.g., Bezzi et al., 1999; Schousboe et al., 1992) and have receptors for many neurotransmitters such as norepinephrine (Shao and Sutin, 1992) and glutamatergic NMDA (Muller et al., 1993), metabotropic (Shelton and McCarthy, 1999) and AMPA receptors (Muller, 1992), all systems implicated in multiple aspects of learning and memory processes. Considering these observations of the interaction between the astrocytes and what would appear to be “synaptic” transmission, it seems likely that for an animal to learn and to remember, there must be plastic changes in glia as well as neurons. Myelination and the Complex Environment 11 Myelination continues well into human adulthood (Yakovlev and Lecours, 1967; Benes et al., 1994), and the first evidence for experience effects on oligodendrocyte development came from Szeligo and Leblond (1977). Subsequently Juraska and Kopcik (1988) found that EC rats had more myelinated axons than IC rats in the splenial corpus callosum. A recent finding (Briones et al., 1999) indicates that experience continues to have dramatic effects on the adult myelination process in the splenial corpus callosum. Subsequent work by Juraska and Kopcik (1988) indicated enhanced myelination of splenial axons in EC rats. Plasticity of Vasculature Perhaps surprisingly, both in terms of earlier reports (e.g., Diamond et al., 1964; Rowan and Maxwell, 1981) and in terms of long held beliefs regarding vascular development (Bar, 1980), the capillary system exhibits two forms of plasticity: Capillaries are both larger, on average, and more frequent, it terms of measures such as the fractional volume of capillaries per neuron, as shown in Figure 1. In fact, on a percentage change per neuron basis, capillaries exhibit far more plasticity than synapses, with an increase of over 80% in volume fraction per neuron in rats placed in complex environments at weaning (Black et al., 1987; Sirevaag et al., 1988). While the greatest capillary plasticity is seen in weanlings, this plasticity continues into adulthood, diminishing with age (Black et al., 1989). 12 Persistence of non-neuronal changes As with those for the addition of synapses (e.g., Camel et al., 1986 ; (Kleim et al., 1997; Briones et al., in preparation), these effects of experience on myelination exhibit a step-wise effect: unlike experience induced changes in glia which appear to fade rapidly once differential experience is discontinued (e.g., Kleim et al., in revision), changes in myelination appear to be stable across a subsequent 30 day period of return to an individual cage housing condition (Briones et al., 1999; Figure 2). It is interesting to speculate that added synapses and myelin are stable because they represent permanent, survival-important additions to the “wiring diagram” of the brain whereas astrocytic and possibly vascular (yet to be tested) changes are adjustments to immediate demands of experience that can be reversed, saving metabolic investment, in the absence of continued environmental pressure. Summary: EC-based description of neuronal & non-neuronal plasticity whether measures of the effects of learning on functional (synaptic) brain organization may already be affected by these nonsynaptic changes The overriding message, in any case, is that the brain is the organ of adaptation—the interface between the individual and its environment. As such it dynamically adjusts to the past demands placed upon it by experience, as if assuming that the experiences of the past must be good predictors of the future. 13 Abraham and Tate (Abraham and Tate, 1997) termed this concept of past experiences predicting, or predisposing the system to subsequent activity as “metaplasticity.” This idea is consistent with a wide-body of literature where seemingly “sub-optimal” patterns of activity have pronounced effects on subsequent responses (e.g., Frey and Morris, 1997). Moreover, technological advances are now revealing that what may once have been thought of as a nonexistent synaptic response was actually the inability to observe the response – just because we didn’t see it doesn’t mean it’s not there. For example, modulation of intracellular pathways (REF) or the insertion/activation of “silent” synapses (Atwood and Wojtowicz, 1999) are mechanisms whereby similar patterns of synaptic activation could produce distinctly different subsequent responses. plasticity not as age-restricted as people believe (vis ctx & cerebellum) I’m not sure where to put this!!! Similarly, these forms of neuronal plasticity occur relatively consistently across the age spectrum and do not appear to be restricted to particular critical or sensitive periods of development. Exposure to a complex environment has been shown to affect dendritic field dimensions in the visual cortex of adult, middle-aged and even elderly rats (e.g., Juraska et al., 1980; Green et al., 1983; Black et al., 1986; Connor et al., 1981). Synapse numbers per neuron are increased in adults placed in complex environments (Briones et al., in preparation). Likewise, cerebellar plasticity (Floeter and Greenough, 1979; 14 Pysh and Weiss, 1979), while not thoroughly studied, seems to occur throughout the lifespan, although this may occur in the context of a decline in elderly animals (e.g., Greenough et al., 1986). What drives the plasticity of brain tissues? here we start to parcel out the dichotomies of trainings that induce plasticity (activity vs. metabolic; learning vs activity; skill vs reach; LTP vs EC). in this section, I see a parallel-structured discussion of whether each specific form of plasticity (within the broader neuronal and non-neuronal categories) was involved in that type of training The existence of short-term and long-term processes of brain cellular adaptation, and the fact that physical activity HAS THE IDEA OF PHYSICAL ACTIVITY INDUCING CHANGES BEEN BROUGHT UP YET? and learning are both involved in the behavioral events that appear to drive these processes, leads to the next natural question: what causes changes in neurons, glia and vasculature. neuronal activity (learning or motor/sensory activity) or more nonspecific (metabolic/endocrine) changes At the topmost level (as opposed, say, to the level of trophic factors or receptor subunits), we can propose two general causal forces at the behavioral level: the general categories of activity and learning. With regard to activity, we have muscle as a model: with sufficient activity, muscle will hypertrophy, the particular details varying with the extent and pattern of activation. One can suppose that activation of brain tissues in association with peripheral activity, via intermediary cellular events, might similarly trigger neuronal, glial or vascular 15 hypertrophy of the sort seen in rats after complex environment housing. With regard to learning, it seems plausible that certain changes in neurons, astrocytes or oligodendrocytes might be learning-specific, although it is harder to imagine that changes in capillaries would play very specific roles in learning. At a broader level, it is also possible to imagine that responses to training such as stress, or related metabolic consequences of behavioral manipulations could lead to changes in brain tissue. Certainly stress can have negative consequences for at least some brain regions (e.g., Sapolsky, 1996), although the adrenal hypertrophy-correlated astroglial changes in the hippocampal formation appear to be dissociated from the experience-correlated visual cortex changes in complex environment research (Sirevaag et al., 1991). early models to tease apart these two chang and greenough ’82 To examine the roles of learning vs. other consequences of training (e.g., activity, stress, etc) on neuronal changes, we have utilized paradigms in which the consequences of learning would be focused in particular regions in the brain for which other regions could serve as control or comparison samples. In one early study, Chang and Greenough (1982) compared rats trained in a complex series of changing maze patterns that learned with either the same eye always occluded or with occlusion of alternate eyes on successive days. In rodents, approximately 90-95% of retinal ganglion cell axons project to the opposite side of the brain (Lund, 1965) such that the unilaterally-trained rats should have most 16 training input restricted to the hemisphere opposite the open eye, whereas the bilaterally-alternating training should have allocated the learning input about equally to both hemispheres. Both groups had been previously subjected to transection of the corpus callosum, a “split-brain” procedure that eliminates communication between the two hemispheres of the brain. Controls were surgically operated and subsequently handled but not trained were divided into unilaterally and bilaterally occluded groups. plasticity (dend. branching) limited to where neural activity occurred The result indicated increased dendritic branching, a correlate of increased synapse number, in both hemispheres of the alternately trained group relative to the non-trained group and in the non-occluded hemisphere of the unilaterally trained group, compared to the occluded hemisphere. This result indicates that either training or training-related activity drives dendritic plasticity. reach training -- again, plasticity (dend. branching) limited to where neural activity occurred Greenough et al. (1985) used unilateral and bilateral training to study the effects of forelimb reaching on plasticity in rat somatosensory-somatomotor cortex of the trained vs. untrained (or activated vs. unactivated) hemisphere. These animals were compared to untrained controls. The results in this study were similar to those of Chang and Greenough (1982): for deep pyramidal neurons of the type that control forelimb activity, dendritic branching was greater in the hemisphere opposite trained forelimbs. For more superficial pyramidal 17 neurons, there were effects of training, but these effects were not restricted to the “trained” side in unilaterally-trained animals do you not want to mention the forked-apicals? (Withers and Greenough, 1989). Taken with the study above, the results indicate that learning or some other aspect of training-related activity drives morphological change in neurons. Both experiments make clear that a generally-acting hormonal or metabolic effect would be expected to alter comparable regions of the brain whether or not they were beinXXXXXXXx Bill, not really sure what you meant to say here…. how to distinguish between learning- and motor/sensory activitybased neural activity?? An obvious issue remaining is that with which we opened this section: whether activity or learning causes structural changes in the brain. AC/VX/IC I’m trying to combine work in cerebellum & motor cortex To address this directly, Black et al. (1990) created adult female rat groups that had 1) a substantial amount of learning with relatively little physical activity (AC below), 2) a substantial amount of physical activity with relatively little learning (FX and VX below) or 3) minimal opportunity for physical activity or learning (IC below). ACrobatic rats (AC) completed a multi-element elevated obstacle course that required learning significant motor skill while providing only limited exercise. Forced eXercise (FX) rats ran on a treadmill, reaching durations of 60 minutes a day, exercising but with very little learning. Voluntary eXercise 18 (VX) rats had access to running wheels attached to their cages and were the only group to exhibit increased heart weight, a sign of aerobic exercise. Inactive Condition (IC) rats were merely removed from their cages for brief daily experimenter handling, providing neither activity nor learning. Results were clear in initial studies focusing on cerebellar cortex. the rest of this segment goes like this…. learning was associated with neuronal changes; activity was associated with non-neuronal changes. (observed in both cerebellar and motor cortex) When the number of synapses per neuron was measured, shown in Figure 3A, the learning group, AC, exceeded the other 3 groups, which did not differ, suggesting that when learning takes place (and not just as a result of neural/motor activity), new synapses are formed. By contrast, as Figure 3B shows, when blood vessel density was measured, the FX and VX groups both had more than the AC or IC groups, which did not differ; this suggests that the formation of new capillaries was driven by neural activity, and not by learning. (the role of this and other non-neuronal changes will be discussed further below) It should be noted that these effects are not limited to cerebellar cortex. Kleim et al. (papers and absts) have described synaptogenesis and changes in synapse morphology in association with the same AC motor learning procedure in the somatosensory-somatomotor forelimb cortex of rats. The first 19 morphological change to occur is, on average, an increase in the size of PSDs, PSD BEEN DEFINED YET? which occurs within one to two days after training begins. Subsequently, at the next day examined, day 5, an increase in the number of synapses per neuron was detected, and the average size of synapses decreased, possibly because the new synapses were, on average, smaller than the pre-existing synapse population. The increase in synapse number was maintained, drifting slowly, but not statistically, upward across the remainder of training. As training progressed, the average size of synapses again increased, possibly suggesting that the new synapses were growing larger or that the population of synapses overall was doing so. A schematic interpretation of these findings appears in Figure 4. There is a long history of evidence for involvement of synapse size changes in plasticity that cannot be reviewed here due to space limitations (is there a Harris or other review to which we could refer?) (Ask Jeff for input on this paragraph.) There is one other interesting thing about these (cerebellar) synapses— many of them involve additional postsynaptic spines contacting presynaptic varicosities on which one or more spines already exist (Federmeier et al., submitted). The implications of this finding for wiring diagram level models of the learning process remain to be determined. It should be noted that this phenomenon is not unique to the cerebellum—we have seen multiple postsynaptic contacts increased on excitatory morphology presynaptic 20 varicosities in the visual cortex of rats reared in complex environments in comparison to individually-caged control rats (Jones et al., 1997). Role of non-neuronal changes in learning / activity based plasticity. – MAINTENANCE!!!! One is Brenda's 1994? Paper showing the correlation between synapse number and astrocyte Vv. The other is Jeff's astrocyte persistence paper. Regulation of Astrocyte Plasticity Is this redundant? This was mentioned in the section on non-neuronal plasticity and perhaps should merely be elaborated more in that section there are two studies that might be discussed in more detail either in that section or here. Tj's ensheathment paper fits in this discussion. The point of putting it here is by way of a segue into a discussion of the tendency to ignore non neuronal (or even nonsynaptic) changes. BILL, IT SEEMS THAT MOST OF THIS PARAGRAPH PROVIDES FURTHER SUPPORT FOR THE NON-GLOBAL (METABOLIC) EFFECT OF ACTIVITY ON PLASTICITY, BUT DOESN’T SAY MUCH ABOUT “DIFFERENT TYPES OF PLASTICITY. MAYBE YOU CAN INTEGRATE IT INTO OTHER PARTS OF THE TEXT, OR MOVE THE WHOLE THING….. Although differential experience can induce widespread plastic changes within the brain, the concept that different kinds of plasticity occur in different situations, and suggests that the type and location of the plasticity is dependent upon the nature of the experience (Morris et al., 1989; Klintsova & Greenough, 21 1999). As discussed above, motor training experiences that involve the development of motor skill induce changes in synapse number within the cerebellar and motor cortices while extensive repetition of unskilled movements causes non-neuronal changes, but no change in synapse number (Black et al., 1990; Kleim et al., 1998c; Kleim et al., 1996; Kleim et al., 2002b). Similarly, the acquisition of skilled forelimb movements causes a reorganization of forelimb movement representations within motor cortex (Nudo et al., 1996; Kleim et al., 1998a) while extensive repetition of unskilled movements (Plautz et al., 2000; Kleim et al., 2002a) and forelimb strength training (Remple et al., 2001) do not. However, strength training does increase synapse number within the ventral spinal cord but motor skill training does not (Kleim et al., 2001). Differential patterns of plasticity can also be observed across different forms of learning. For example, complex motor skill training does not alter synapse number within the deep cerebellar nuclei (Kleim et al., 1998b) whereas eye blink conditioning does (Bruneau et al., 2001). BUT WHO IS SAYING THAT THESE DIFFERENT FORMS OF ACTIVITY ARE UTILIZING THE SAME AREAS??? CAN WE BE MORE SPECIFIC ABOUT “DEEP CEREBELLAR NUCLEUS”?? Even within a specific learning experience plasticity can be found within some brain regions but not others. DOESN’T THIS SIMPLY SAY THAT NOT ALL BRAIN AREAS ARE INVOLVED IN ALL BEHAVIORS? Complex housing causes dendritic hypertrophy in visual and sensory cortices but not in prefrontal or temporal cortex (Kolb ref). SAME ISSUE AS ABOVE. Skilled forelimb reach training causes a reorganization of movement representations and an increase in synapse number 22 within the caudal forelimb area but not within the neighboring rostral forelimb area (Kleim et al., 2002b). THIS SEEMS OUT OF PLACE, IMPORTANT, BUT NOT IN THE RIGHT SPOT . Interestingly, reach training induced increase of field potential in forelimb contralateral to preferred limb (vs. ipsilateral) in layer II/III (Rioult-Pedotti, 1998 #179), suggesting a selective strengthening of horizontal cortical connections associated with learning new motor skill. Complex motor training is associated with an increase in synapse number within the cerebellar cortex (Kleim et al., 1998c) but not within the deep cerebellar nuclei (Kleim et al., 1998b). REDUNDANT FROM ABOVE. The specificity of the plasticity can even be reduced to subpopulations of neurons within the same brain region. For example, complex housing causes dendritic hypertrophy within cerebellar Purkinje cells but not granule cells (Floeter and Greenough, 1979). Reach training causes dendritic hypertrophy within layer II/III of the motor cortex that is restricted to a specific class of pyramidal cells (Withers and Greenough, 1989). Finally, plasticity can even be observed to be restricted to specific afferents onto individual neurons. Complex motor skill training causes an increase in parallel fiber synapses onto Purkinje cells but not climbing fibers (Kleim et al., 1998c). Eyeblink conditioning causes an increase in the number of excitatory synapses within the anterior interpositus without alter inhibitory synapse number (Bruneau et al., 2001). Similarly strength training causes an increase in excitatory but not inhibitory axosomatic synapses within the ventral spinal cord (Kleim et al., 2001). THESE CONCEPTS SEEMS TO GO WITH THIS SECTION: 23 Synaptic specificity supported by “synaptic tag” that is localized and protein-synthesis independent (Frey, 1997 #56). Fits concept of metaplasticity in that history of synapse (even sub optimal stimulation patterns) pre-disposes synapse to subsequent modification. Could consider integrating notion of differential parameters necessary/sufficient to induce LTP (emphasize model of learning, not that it is equivalent or necessary for) in multiple areas of the brain. That one type of stimulus does not result in the same effect in numerous areas of the brain suggests (obviously) differential make-up of that area and surely different mechanisms. This notion would simply parallel our argument of different “types of plasticity” (as defined anatomically), with physiological correlates (Yun, 2002 #106; Trepel, 1998 #99). these next two sections seem out of place now….. This goes on the end or might be placed elsewhere: A note on Long-term potentiation Engert and Bonhoeffer have reported apparent synaptogenesis in vitro in association with LTP induction. High-frequency stimulation produced enhanced growth of filopodia-like protrusions in CA1 slices (viewed with 2-photon), an effect that was blocked by NMDAR antagonism (Maletic-Savatic, 1999 #180). ALSO WORK OF ANDERSEN AND SOLENG (Andersen, 1998 #181) WHO SHOWED SYNAPTOGENESIS ASSOCIATED WITH LTP AND SPATIAL 24 LEARNING (THEY SUGGESTED BIFURCATION/BRANCHING OF EXISTING SPINES) At least 3 studies, HOWEVER, dissociate LTP from spatial behavior and morphological change. The primary point I want to make is the apparent dissociation of LTP from EC effects on synapses published by J. Tsien in Nature Neuroscience. This suggests that LTP and synaptogenesis are independent phenomena. I am not sure what the range of the evidence is or the weight of it (e.g., other more recent work that bears on this issue, most of which are likely to have cited both of the above studies (Tsien and E-B) and hence should be locatable via the science citation index, which I have not used for the last million years), but the dissociation to me seems most powerful-synapse addition may mediate LTP, but synapse addition need not involve an LTP-like process for its induction. On the Horizon: A Role for Protein Synthesis at the synapse Since the first report of morphological evidence for protein synthesis at the synapse (Steward & Levy, 1992) there has been a growing literature investigating this phenomenon. Synaptic and dendritic protein synthesis have been shown to be activated by metabotropic glutamate receptors in some cases (e.g., Weiler & Greenough, 1993; Weiler et al., 1994, 1997; Eberwine PNAS-still in press?) and by NMDA receptors as well (Sheetz et al., 2000). Proteins synthesized at synapses include the fragile X protein FMRP and 25 calcium/calmodulin-dependent protein kinase II (CAMKII). FMRP has also been shown to be necessary for the mGluR-dependent synthesis, which is not observed in FMR1 knockout mice (cite Spangler abstract). Plasticity-inducing forms of electrical stimulation have been shown to trigger the transcription and transport of mRNA for the protein ARC to dendritic sites of stimulation, where it is translated (Steward and Worley references). mGluR1 activation, ARC synthesis and CAMKII activity have been proposed to be involved in various forms of plasticity (Huber/Bear work; Steward; Mary Kennedy), although details of the specific functions of synaptic or dendritic protein synthesis are still under investigation. Do you think we need to say anything more here? The chapter is really not "about" this, and I am not sure (but open to suggestions) what additional data makes sense to include. The principal thing I want to add at this point is a summary that comes back to the main point of the chapter--that we are only looking at a small portion of what the brain does when it accomplishes plastic change. I really would like your feedback on the earlier stuff. I have attached a copy of the chapter file as it exists on my computer. There is a demarcated line below which all of my additions occur, so it should be possible to just paste what you have and the part that I added together. ANOTHER “TYPE” OF PLASTICITY TO CONSIDER: NEUROGENESIS. 26 Housing in an complex environment resulted in enhanced survival of “new neurons” (aka, neurogenesis) (tested 4 weeks later) but no effect on number generated (tested 1 day after BrdU injection) (Nilsson, 1999 #83). Neurogenesis rate is doubled in dentate following training on an associative learning task requiring hippocampus (Gould, 1999 #183). DO WE WANT TO DISCUSS ANY SORT OF TEMPORAL COMPONENT THAT COULD DIFFERENTIALLY INFLUENCE THE “TYPE” OF PLASTICITY GOING ON? FOR EXAMPLE: Consider temporal component of morphological changes. For example, following one-trial learning, the density of axospinous synapses was increased 77% in IMHV of chicks and PSD (measured by “height” of synapse) was decreased at 1 HR post training. Yet 24-hours later there were no differences (Doubell, 1993 #184). Of course this is consistent with Kleim work, possibly integrate this study with that section??? STRUCTURE-FUNCTION RELATIONSHIP, NEEDS TO BE INCORPORATED SOMEWHERE: Housing in complex environment resulted in 50% increase in somatotopic representation of forepaw, most of which came from glaborous surface and more specifically, from digit tips (Coq, 1998 #53). Primary neurons and the cortex: Is the current approach overly-restrictive? 27 Historically, investigations into neuronal plasticity have focused, almost exclusively, on modifications in the structure and function of primary neurons and circuits. While the importance of these systems can not be overlooked, it belies the fact that neurons not directly involved in such pathways far out number those that do. Seress et al. (Seress, 2001 #92) have reported that 95% of terminals forming asymmetric synapses with parvalbumin-positive dendrites in the dentate and strata pyramidale and lucidum of CA3 originated from granule cells. SO WHY DO WE ALWAYS LOOK @ PYRAMIDAL CELLS? Modification of “modulatory” neurons can have dramatic effects on the function of primary neurons. For example, receptive field size in sensory cortex has been shown to be sensitive to pharmacological disinhibition (Tremere, 2001 #185; Tremere, 2001 #186; Jacobs, 1991 #187). The source of such inhibition likely stems from extragranular layers of cortex as rapid (physiologically-defined) changes in both visual (Trachtenberg, 2000 #188; Trachtenberg, 2001 #189) and somatosensory cortices (Diamond, 1994 #190) have been reported to occur prior to the expression of modifications in layer IV. Finally, observations by Gilbert and colleagues (Gilbert, 1979 #191; Gilbert, 1992 #192) further suggest that horizontal connections may be the source of such changes in visuo- and topographic-maps. The cerebral cortex is often-times considered “where” changes occur, ignoring subcortical contributions and importance. Numerous changes outside cortex such as striatum (Comery, 1995 #21; Comery, 1996 #22), spinal cord 28 (Devor, 1978 #193), temporal dynamics of change are distributed across the neuroaxis (Faggin, 1997 #194), In summary, brain plasticity appears to be a phenomenon that is not restricted to elements that are neuron-specific. In fact, it could be argued that neuronal plasticity is but a small fraction of the overall changes that occur in response to experience and that we are just beginning to understand the importance of these other forms of brain plasticity. Blah, blah, blah. CHAPTER WORKING NOTES: MSVs—Kara; TJ; specialized synaptic morph changes. Tissue cultures lacking astrocytes—how good a model? Lack of synapse formation in cultures without astrocytes (Ullian, 2001 #100). Moreover, even when synapses do form, they are functionally immature. Obvious implications on studies of “synaptic plasticity” in vitro. Lack of astro part of ECM. Lack of basis for TPA, other actions probably involved in synaptogenesis. MMP3, MMP6, MMP9 (Metalomatrix proteins), stromolysin, gelatinase. Roles of Astros, ECM, TPA, etc. in synaptogenesis; adhesions; rec aggregation Incorporate Harris, Matus, Segal. Motility and shape issues. Put together a model, slow accumulation of synapses via overproduction-selection as a basis for the stable long-term substrate of memory; plus fast shape changes, PSD size, 29 perfs, interpret multiple synapses from local and wiring diagram view. NOT SURE WE HAVE TIME FOR THIS NOR IS THIS NECESSARILY CONSISTENT WITH UNDERLYING THEME OF THE PAPER. 30 Abraham, W. C. and Tate, W. P. (1997) Metaplasticity: a new vista across the field of synaptic plasticity. Prog Neurobiol 52, 303-23. Anderson, B. J., Li, X., Alcantara, A. A., Isaacs, K. R., Black, J. E. and Greenough, W. T. (1994) Glial hypertrophy is associated with synaptogenesis following motor-skill learning, but not with angiogenesis following exercise. Glia 11, 73-80. Araque, A., Parpura, V., Sanzgiri, R. P. and Haydon, P. G. (1998) Glutamatedependent astrocyte modulation of synaptic transmission between cultured hippocampal neurons. Eur J Neurosci 10, 2129-42. Araque, A., Parpura, V., Sanzgiri, R. P. and Haydon, P. G. (1999) Tripartite synapses: glia, the unacknowledged partner. Trends Neurosci 22, 208-15. Atwood, H. L. and Wojtowicz, J. M. (1999) Silent synapses in neural plasticity: current evidence. Learn Mem 6, 542-71. Bailey, C. H. and Chen, M. (1988) Long-term sensitization in Aplysia increases the number of presynaptic contacts onto the identified gill motor neuron L7. Proc Natl Acad Sci U S A 85, 9356-9. Bar, T. (1980) The Vascular System of the Cerebral Cortex. Springer: Berlin. Benes, F. M., Turtle, M., Khan, Y. and Farol, P. (1994) Myelination of a key relay zone in the hippocampal formation occurs in the human brain during childhood, adolescence, and adulthood. Arch Gen Psychiatry 51, 477-84. Bennett, E. L., Diamond, M. C., Krech, D. and Rosenzweig, M. R. (1964) Chemical and anatomical plasticity of brain. Science 146, 610-619. 31 Bezzi, P., Vesce, S., Panzarasa, P. and Volterra, A. (1999) Astrocytes as active participants of glutamatergic function and regulators of its homeostasis. Adv Exp Med Biol 468, 69-80. Black, J. E., Isaacs, K. R., Anderson, B. J., Alcantara, A. A. and Greenough, W. T. (1990) Learning causes synaptogenesis, whereas motor activity causes angiogenesis, in cerebellar cortex of adult rats. Proc Natl Acad Sci U S A 87, 5568-72. Black, J. E., Parnisari, R., Eichbaum, E. and Greenough, W. T. (1986) Morphological effects of housing environment and excersize on cerebral cortex and cerebellum of old rats. Society for Neuroscience Abstracts 12, 1579. Black, J. E., Polinsky, M. and Greenough, W. T. (1989) Progressive failure of cerebral angiogenesis supporting neural plasticity in aging rats. Neurobiol Aging 10, 353-8. Black, J. E., Sirevaag, A. M. and Greenough, W. T. (1987) Complex experience promotes capillary formation in young rat visual cortex. Neurosci Lett 83, 3515. Bliss, T. V. and Lomo, T. (1973) Long-lasting potentiation of synaptic transmission in the dentate area of the anaesthetized rabbit following stimulation of the perforant path. J Physiol 232, 331-56. Briones, T., Shah, P., Juraska, J. and Greenough, W. T. (1999) Effects of prolonged exposure to and subsequent removal from a complex environment 32 on corpus callosum myelination in the adult rat. Society for Neuroscience Abstracts 25, 638. Briones, T. L., Klintsova, A. Y. and Greenough, W. T. ((in preparation)) Stability of synaptic plasticity induced by complex environment exposure in the adult rat visual cortex. . Bruneau, R., Zook, A., Walters, D., Nolan, B. C., Cooper, N., Freeman, J. H. and Kleim, J. A. (2001) Synaptogenesis within anterior interpositus nucleus following eyeblink conditioning. Society for Neuroscience Abstracts 27, 1689. Camel, J. E., Withers, G. S. and Greenough, W. T. (1986) Persistence of visual cortex dendritic alterations induced by postweaning exposure to a "superenriched" environment in rats. Behav Neurosci 100, 810-3. Chang, F. L. and Greenough, W. T. (1982) Lateralized effects of monocular training on dendritic branching in adult split-brain rats. Brain Res 232, 283-92. Comery, T. A., Shah, R. and Greenough, W. T. (1995) Differential rearing alters spine density on medium-sized spiny neurons in the rat corpus striatum: evidence for association of morphological plasticity with early response gene expression. Neurobiol Learn Mem 63, 217-9. Comery, T. A., Stamoudis, C. X., Irwin, S. A. and Greenough, W. T. (1996) Increased density of multiple-head dendritic spines on medium-sized spiny neurons of the striatum in rats reared in a complex environment. Neurobiol Learn Mem 66, 93-6. 33 Connor, J. R., Melone, J. H., Yuen, A. R. and Diamond, M. C. (1981) Dendritic length in aged rats' occipital cortex: an environmentally induced response. Exp Neurol 73, 827-30. Dani, J. W., Chernjavsky, A. and Smith, S. J. (1992) Neuronal activity triggers calcium waves in hippocampal astrocyte networks. Neuron 8, 429-40. Diamond, M. C., Krech, D. and Rosenzweig, M. R. (1964) The effects of an enriched environment on the histology of the rat cerebral cortex. Journal of Comparative Neurology 123, 111-120. Diamond, M. C., Law, F., Rhodes, H., Lindner, B., Rosenzweig, M. R., Krech, D. and Bennett, E. L. (1966) Increases in cortical depth and glia numbers in rats subjected to enriched environment. J Comp Neurol 128, 117-26. Fiala, J. C., Allwardt, B. and Harris, K. M. (2002) Dendritic spines do not split during hippocampal LTP or maturation. Nat Neurosci 5, 297-8. Floeter, M. K. and Greenough, W. T. (1979) Cerebellar plasticity: modification of Purkinje cell structure by differential rearing in monkeys. Science 206, 227-9. Frey, U. and Morris, R. G. (1997) Synaptic tagging and long-term potentiation. Nature 385, 533-6. Geinisman, Y., Berry, R. W., Disterhoft, J. F., Power, J. M. and Van der Zee, E. A. (2001) Associative learning elicits the formation of multiple-synapse boutons. J Neurosci 21, 5568-73. Geinisman, Y., deToledo-Morrell, L. and Morrell, F. (1991) Induction of long-term potentiation is associated with an increase in the number of axospinous synapses with segmented postsynaptic densities. Brain Res 566, 77-88. 34 Geinisman, Y., Morrell, F. and de Toledo-Morrell, L. (1990) Increase in the relative proportion of perforated axospinous synapses following hippocampal kindling is specific for the synaptic field of stimulated axons. Brain Res 507, 325-31. Green, E. J., Greenough, W. T. and Schlumpf, B. E. (1983) Effects of complex or isolated environments on cortical dendrites of middle-aged rats. Brain Res 264, 233-40. Greenough, W. T., Larson, J. R. and Withers, G. S. (1985) Effects of unilateral and bilateral training in a reaching task on dendritic branching of neurons in the rat motor-sensory forelimb cortex. Behav Neural Biol 44, 301-14. Greenough, W. T., McDonald, J. W., Parnisari, R. M. and Camel, J. E. (1986) Environmental conditions modulate degeneration and new dendrite growth in cerebellum of senescent rats. Brain Res 380, 136-43. Greenough, W. T., West, R. W. and DeVoogd, T. J. (1978) Subsynaptic plate perforations: changes with age and experience in the rat. Science 202, 10968. Hart, B. and Risley, T. R. (1995) Meaningful Differences in the Everyday Experience of Young American Children. Brookes Publishing: Baltimore. Hatton, G. I. (1997) Function-related plasticity in hypothalamus. Annu Rev Neurosci 20, 375-97. Hebb, D. O. (1949) The organization of behavior. Wiley: New York. Jones, D. G. and Calverley, R. K. (1991) Frequency of occurrence of perforated synapses in developing rat neocortex. Neurosci Lett 129, 189-92. 35 Jones, T. A., Chu, C. J., Grande, L. A. and Gregory, A. D. (1999) Motor skills training enhances lesion-induced structural plasticity in the motor cortex of adult rats. J Neurosci 19, 10153-63. Jones, T. A. and Greenough, W. T. (1996) Ultrastructural evidence for increased contact between astrocytes and synapses in rats reared in a complex environment. Neurobiol Learn Mem 65, 48-56. Jones, T. A., Klintsova, A. Y., Kilman, V. L., Sirevaag, A. M. and Greenough, W. T. (1997) Induction of multiple synapses by experience in the visual cortex of adult rats. Neurobiol Learn Mem 68, 13-20. Juraska, J. M., Greenough, W. T., Elliott, C., Mack, K. J. and Berkowitz, R. (1980) Plasticity in adult rat visual cortex: an examination of several cell populations after differential rearing. Behav Neural Biol 29, 157-67. Juraska, J. M. and Kopcik, J. R. (1988) Sex and environmental influences on the size and ultrastructure of the rat corpus callosum. Brain Res 450, 1-8. Kleim, J. A., Barbay, S., Cooper, N. R., Hogg, T. M., Reidel, C. N., Remple, M. S. and Nudo, R. J. (2002a) Motor learning-dependent synaptogenesis is localized to functionally reorganized motor cortex. Neurobiol Learn Mem 77, 63-77. Kleim, J. A., Barbay, S. and Nudo, R. J. (1998a) Functional reorganization of the rat motor cortex following motor skill learning. J Neurophysiol 80, 3321-5. Kleim, J. A., Bruneau, R., Remple, M., Soroka, N. and Cooper, N. (2001) Forelimb strength training leads to increased synapse number within the ventral spinal cord of the rat. Society for Neuroscience Abstracts 27. 36 Kleim, J. A., Cooper, N. R. and VandenBerg, P. (2002b) Exercise induces angiogenesis but does not alter movement representations within rat motor cortex. Brain Research In Press. Kleim, J. A., Lussnig, E., Schwarz, E. R., Comery, T. A. and Greenough, W. T. (1996) Synaptogenesis and Fos expression in the motor cortex of the adult rat after motor skill learning. J Neurosci 16, 4529-35. Kleim, J. A., Pipitone, M. A., Czerlanis, C. and Greenough, W. T. (1998b) Structural stability within the lateral cerebellar nucleus of the rat following complex motor learning. Neurobiol Learn Mem 69, 290-306. Kleim, J. A., Swain, R. A., Armstrong, K. A., Napper, R. M., Jones, T. A. and Greenough, W. T. (1998c) Selective synaptic plasticity within the cerebellar cortex following complex motor skill learning. Neurobiol Learn Mem 69, 27489. Kleim, J. A., Vij, K., Ballard, D. H. and Greenough, W. T. (1997) Learningdependent synaptic modifications in the cerebellar cortex of the adult rat persist for at least four weeks. J Neurosci 17, 717-21. Kleim, J. A., Vij, K., Kelly, J. L., Ballard, D. H. and Greenough, W. T. ((In revision)) The persistence of training-induced astrocytic hypertrophy within the cerebellar cortex. . Lund, R. D. (1965) Uncrossed visual pathways of hooded and albino rats. Science 149, 1506-7. Lynch, G., Deadwyler, S. and Cotman, G. (1973) Postlesion axonal growth produces permanent functional connections. Science 180, 1364-6. 37 Meshul, C. K., Seil, F. J. and Herndon, R. M. (1987) Astrocytes play a role in regulation of synaptic density. Brain Res 402, 139-45. Moser, M. B., Trommald, M. and Andersen, P. (1994) An increase in dendritic spine density on hippocampal CA1 pyramidal cells following spatial learning in adult rats suggests the formation of new synapses. Proc Natl Acad Sci U S A 91, 12673-5. Muller, C. M. (1992) A role for glial cells in activity-dependent central nervous plasticity? Review and hypothesis. Int Rev Neurobiol 34, 215-81. Muller, T., Grosche, J., Ohlemeyer, C. and Kettenmann, H. (1993) NMDAactivated currents in Bergmann glial cells. Neuroreport 4, 671-4. Nudo, R. J., Milliken, G. W., Jenkins, W. M. and Merzenich, M. M. (1996) Usedependent alterations of movement representations in primary motor cortex of adult squirrel monkeys. J Neurosci 16, 785-807. Plautz, E. J., Milliken, G. W. and Nudo, R. J. (2000) Effects of repetitive motor training on movement representations in adult squirrel monkeys: role of use versus learning. Neurobiol Learn Mem 74, 27-55. Raisman, G. and Field, P. M. (1973) A quantitative investigation of the development of collateral reinnervation after partial deafferentation of the septal nuclei. Brain Res 50, 241-64. Ramon y Cajal, S. (1893) New findings about the histological structure of the central nervous system. Archiv fur Anatomie und Physiologie (Anatomie), 319-428. 38 Remple, M. S., Bruneau, R. M., VandenBerg, P. M., Goertzen, C. and Kleim, J. A. (2001) Sensitivity of cortical movement representations to motor experience: evidence that skill learning but not strength training induces cortical reorganization. Behav Brain Res 123, 133-41. Rouach, N., Glowinski, J. and Giaume, C. (2000) Activity-dependent neuronal control of gap-junctional communication in astrocytes. J Cell Biol 149, 151326. Rowan, R. A. and Maxwell, D. S. (1981) Patterns of vascular sprouting in the postnatal development of the cerebral cortex of the rat. Am J Anat 160, 24755. Salm, A. K. (2000) Mechanisms of glial retraction in the hypothalamoneurohypophysial system of the rat. Exp Physiol 85, 197S-202S. Sapolsky, R. M. (1996) Stress, Glucocorticoids, and Damage to the Nervous System: The Current State of Confusion. Stress 1, 1-19. Schousboe, A., Westergaard, N., Sonnewald, U., Petersen, S. B., Yu, A. C. and Hertz, L. (1992) Regulatory role of astrocytes for neuronal biosynthesis and homeostasis of glutamate and GABA. Prog Brain Res 94, 199-211. Shao, Y. and Sutin, J. (1992) Expression of adrenergic receptors in individual astrocytes and motor neurons isolated from the adult rat brain. Glia 6, 108-17. Shelton, M. K. and McCarthy, K. D. (1999) Mature hippocampal astrocytes exhibit functional metabotropic and ionotropic glutamate receptors in situ. Glia 26, 1-11. 39 Sirevaag, A. M., Black, J. E. and Greenough, W. T. (1991) Astrocyte hypertrophy in the dentate gyrus of young male rats reflects variation of individual stress rather than group environmental complexity manipulations. Exp Neurol 111, 74-9. Sirevaag, A. M., Black, J. E., Shafron, D. and Greenough, W. T. (1988) Direct evidence that complex experience increases capillary branching and surface area in visual cortex of young rats. Brain Res 471, 299-304. Sirevaag, A. M. and Greenough, W. T. (1988) A multivariate statistical summary of synaptic plasticity measures in rats exposed to complex, social and individual environments. Brain Res 441, 386-92. Sirevaag, A. M. and Greenough, W. T. (1991) Plasticity of GFAP-immunoreactive astrocyte size and number in visual cortex of rats reared in complex environments. Brain Res 540, 273-8. Smit, A. B., Syed, N. I., Schaap, D., van Minnen, J., Klumperman, J., Kits, K. S., Lodder, H., van der Schors, R. C., van Elk, R., Sorgedrager, B., Brejc, K., Sixma, T. K. and Geraerts, W. P. (2001) A glia-derived acetylcholine-binding protein that modulates synaptic transmission. Nature 411, 261-8. Szeligo, F. and Leblond, C. P. (1977) Response of the three main types of glial cells of cortex and corpus callosum in rats handled during suckling or exposed to enriched, control and impoverished environments following weaning. J Comp Neurol 172, 247-63. 40 Tanzi, E. (1893) Facts and inductions in current histology of the nervous system. Rivista sperimentale di freniatria e medicina legale delle mentali alienazioni 19, 419-472. Toni, N., Buchs, P. A., Nikonenko, I., Bron, C. R. and Muller, D. (1999) LTP promotes formation of multiple spine synapses between a single axon terminal and a dendrite. Nature 402, 421-5. Turner, A. M. and Greenough, W. T. (1985) Differential rearing effects on rat visual cortex synapses. I. Synaptic and neuronal density and synapses per neuron. Brain Res 329, 195-203. Volkmar, F. R. and Greenough, W. T. (1972) Rearing complexity affects branching of dendrites in the visual cortex of the rat. Science 176, 1145-7. West, R. W. and Greenough, W. T. (1972) Effect of environmental complexity on cortical synapses of rats: preliminary results. Behav Biol 7, 279-84. Withers, G. S. and Greenough, W. T. (1989) Reach training selectively alters dendritic branching in subpopulations of layer II-III pyramids in rat motorsomatosensory forelimb cortex. Neuropsychologia 27, 61-9. Yakovlev, P. and Lecours, A. (1967) The myelinogenetic cycles of regional maturation of the brain. In: Regional Development of the Brain Early in Life, pp. 3-70. Ed. A. Minkowski. Blackwell Scientific Publications Inc: Boston, Mass. 41