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Joshua A. Gordon 1 Cellular Mechanisms of Visual

Department of Physiology Cortical Plasticity: A Game of Keck Center for Integrative Neuroscience and Mouse University of California San Francisco, California 94143-0444

Introduction The remarkably complex and precise pattern of connections that characterizes the mammalian arises during development through the equally remarkable process of activity-dependent plasticity: Over time, the visual system learns to see. The role of activity in the development of connectivity in the visual system has been explored in detail in the primary of and monkeys, where initially overlapping inputs from the two segregate into ocular dominance columns during a (Rakic 1976, 1977; LeVay et al. 1978, 1980). Manipulations of visual experience during this critical period have demonstrated that an activity-dependent, correlation-based competition between inputs underlies this segregation (Shatz 1990; Katz and Shatz 1996). Indeed, the correlation-based or "Hebbian" nature of this competitive plasticity underscores the similarity between the processes of development and learning (Hebb 1949; Kandel and O'Dell 1992). Although the rules governing activity-dependent development are well described, the cellular mechanisms by which patterns of neuronal activity are transduced into patterns of synaptic connectivity remain poorly understood. Cellular models of synaptic plasticity have suggested numerous candidate mechanisms, but the lack of effective and specific pharmacological tools has hindered the study of these mechanisms in plasticity in vivo. Recently, however, gene targeting techniques have enabled the generation of a large and growing number of mouse lines, each possessing specific genetic lesions (Brandon et al. 1995; see also http://biomednet.com/mko.htm). These tools are ideal for exploring the roles of particular molecules, and the cellular processes that require them, in complex phenomena that can be studied only in whole animal preparations. Using these tools, of course, requires an appropriate mouse model. Recent experiments, reviewed here, have established the utility of a mouse model of visual cortical plasticity for furthering understanding of the molecular mechanisms of activity-dependent development. Although many aspects of the visual system in the mouse are different from that of higher , appears to occur by a similar process (Dr~iger 1975, 1978; Gordon and Stryker 1996). Experiments testing the effects of single gene mutations have begun to provide insight into cellular mechanisms (Gordon 1995; Hensch et al. 1995; Gordon et al. 1996a,b; T.K. Hensch, J.A. Gordon, E.P. Brandon, G.S. McKnight, R.L. Idzerda, and M.P. Stryker, in prep). These early results, along with the promise of more sophisticated genetic manipulations, suggest that the study of visual cortical plasticity in mice will be a powerful means to

1Present address: New York State Psychiatric Institute, Columbia/Presbyterian Medical Center, New York, New York 10032.

LEARNING & MEMORY 4:245-261 91997 by Cold Spring Harbor Laboratory Press ISSN1072-0502/97 $5.00

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elucidate the cellular mechanisms underlying activity-dependent plasticity during development.

Visual Cortical Plasticity in Cat and Mouse

OCULAR DOMINANCE During the first several weeks of a kitten's life, inputs to cortex carrying PLASTICITY IN THE CAT information from the two eyes segregate into separate patches called ocular dominance columns (LeVay et al. 1978). This process can be prevented by blocking retinal activity (Stryker and Harris 1986). The important component of activity necessary for driving segregation appears to be the correlation between inputs from one relative to the other. This has been demonstrated by experiments aimed at altering the correlation between inputs from the two eyes during the time when columns normally form. Thus, surgically induced strabismus reduces the correlation between inputs from the two eyes and accentuates ocular dominance column segregation (Shatz et al. 1977; L6wel and Singer 1993; L6wel 1994). Coincident electrical stimulation of both optic nerves, which creates perfectly correlated discharge of inputs from the two eyes, prevents column formation (Stryker and Strickland 1984; Stryker 1986). The interpretation of these and other studies, supported by theoretical work, is that simultaneously active inputs successfully activate their common targets; this conjoint pre- and postsynaptic activity strengthens these coactive inputs, stabilizing them within local domains (von der Malsburg 1979; Miller et al. 1989b; Fregnac et al. 1994). The nature of this so-called ocular dominance plasticity has been further studied by manipulating the visual experience of developing kittens. Four basic principles have emerged from such experiments. First, brief monocular visual deprivation causes a profound decrease in both the anatomical spread and the physiologic effectiveness of inputs from the deprived eye onto cortical (Wiesel and Hubel 1963; Olson and Freeman 1975, 1980; Movshon and Dfirsteler 1977; Shatz and Stryker 1978). Second, these effects occur only if the deprivations take place during a critical period early in the development of the animal (Hubel and Wiesel 1970; Olson and Freeman 1980). Third, competition from the open eye is required to drive away responses from the deprived eye, as binocular deprivations of similar duration produce a much smaller effect on visual responses (Wiesel and Hubel 1965; Freeman et al. 1981). Finally, as discussed above, a correlation-based mechanism tmderlies ocular dominance plasticity. This principle can be demonstrated physiologically as well as anatomically. Strabismus and alternating both reduce the degree of correlation between inputs from the two eyes. Inputs from different eyes are thus less likely to be coactive and less likely to be stabilized onto the same postsynaptic . These manipulations therefore reduce the number of binocular cortical cells (Hubel and Wiesel 1965; Blakemore 1976; Blasdel and Pettigrew 1979; Presson and Gordon 1979).

OCULAR DOMINANCE AND Careful study of the physiological effects of visual deprivation in young PLASTICITY IN MOUSE mice reveals a plasticity that obeys these four principles. The murine VISUAL CORTEX visual system contains the same basic structural elements for integration

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VISUAL CORTICAL PLASTICITY IN CATS AND MICE

of inputs from the two eyes as does the cat, the principle difference being the smaller proportion of binocular overlap in the smaller . Only the frontal 30-40 ~ of the upper portion of each visual hemifield is seen by the of both eyes (Dfiiger 1975; Wagor et al. 1980). Retinal ganglion cell representing this region project to eye-specific areas within the dorsal lateral geniculate nucleus (LGN) (M~tin et al. 1983; Godement et al. 1984). These geniculate cells project in turn to the lateral one-third of primary visual cortex, called the binocular zone (Dr~iger 1974, 1975, 1978; Caviness 1975; Wagor et al. 1980; Simmons et al. 1982). Within this zone, nearly all neurons respond to stimuli presented to either eye, although contralateral eye inputs tend to drive most cells more strongly than do ipsilateral inputs (Fig. 1, bottom; Dr~iger 1975, 1978; M~tin et al. 1988; Gordon and Stryker 1996). A key difference with regard to the cat, and a worthy target of future investigation, is the lack of demonstrable ocular dominance columns within the binocular zone (Dr~iger 1974, 1978). Indeed, monocular deprivation in mice fails to affect the anatomic spread of inputs from the deprived eye (Dr/iger 1978). Nevertheless, physiological ocular dominance plasticity can be demonstrated in mice. Brief monocular visual deprivation in young mice dramatically decreases the responsiveness of binocular zone neurons to inputs from the closed eye (Dffa'ger 1978; Gordon and Stryker 1996). After as little as 4 days of monocular lid suture, the influence of the closed eye diminishes: In the ipsilateral hemisphere, responses to the deprived eye nearly disappear, whereas in the contralateral hemisphere, most cells become dominated by the ipsilateral, open eye (see Fig. 1, bottom).

0.4 0.8 I o6 0.4060"810.1 4 Cats 0.2 0.4 Olo 0.1 29 28 0.2 0"21 r~ 1 322 0 ~ tltt 0 i 0 1 i 1 2 3 4 5 6 7 1234567 1 2 3 4 5 6 7 Normal Ipsi-deprived Contra-deprived 0.8 56 0.89 0.410.46 0.3 45 0.6 L Mice o.2 26 0.4 o.~ ] ~3 ~

0.1 0.1 0 0 t ~ I I I tz,_z_oo 1 2 3 4 5 6 7 1 2 3 4 5 6 7 0 I 1 2 3 4 5 6 7 "~'Contra Ipsi'~ -~-Contra Ipsi-I~ 9,~-Contra Ipsi-I~" Figure 1: Comparison of the effects of monocular deprivation in cats and mice. Histograms of ocular dominance scores of neurons recorded from the primary visual cortex of normal and monocularly deprived cats (top) and mice (bottom). Separate histograms are shown for neurons recorded from the cortex ipsilateral (Ipsi, middle) and contralateral (Contra, right) to the deprived eye. The number of neurons in each class is shown above each bar. The contralateral bias index, a weighted average of each histogram, is shown for each histogram. Shifts in the histograms toward the right represent increasing dominance by the ipsilateral eye; shifts toward the left represent increasing dominance by the contralateral eye. Note that significant shifts toward the open eye are seen in the mouse, although these shifts are smaller than those in the cat. Cat data are from Shatz and Stryker (1978); mouse data are from Gordon and Stryker (1996).

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Longer deprivations do not have a greater effect (Dr/iger 1978; Gordon and Stryker 1996). In the mouse, as in the cat, monocular deprivation exerts its effects only within a well-defined critical period, and results from a correlation-based competition between open and closed eye inputs. The murine critical period, defined using 4-day deprivations, extends from P19 through P32, peaking at or near P28; brief deprivations after this period have no effect [Fig. 2; Gordon and Stryker 1996. The timing of the murine critical period is similar to that described recently for the (Fagiolini et al. 1994)]. Binocular deprivation for 4 days at the peak of the critical period has no significant effect on responses, demonstrating the requirement for competition (Gordon and Stryker 1996). Finally, alternating monocular deprivation, after an initial period of contralateral eye deprivation to overcome its normal bias, results in a decrease in the number of binocular cells, demonstrating the correlation-based nature of the competition (Fig. 2; Gordon and Stryker 1996).

A 0.8 ,Critical Period: Mice T B 0.6] ~ Critical Period: Cats 0.7~ :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::?::-:::i:::~i::i::::::::::::::::::::::::::::::::::::

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0.2 ~ 0.2 24 31 26 f5 0.1 0ii L 0 o 1 2 3 4 5 6 7 1 2 3 4 5 6 7 -91--Contra. .Ipsi-~- -qI-Contra Ipsi-~- Ocular Dominance Figure 2: Critical period and the effects of alternating monocular deprivation. (A,B) Critical period for the effects of monocular deprivation in mice (A) and cats (B). The bias index is plotted vs. the age at which deprivation was begun. A lower bias index indicates increasing dominance by the nondeprived eye. Data in A were taken from Gordon and Stryker (1996); the mean+s.D, of five animals at each time point is shown. The range of bias indices from normal animals is indicated by the filled bar. Data in B were taken from Olson and Freeman (1980). The bias index of one animal at each time point is shown. The bias index in normal animals would be -0.5. The bias index was calculated as in Gordon and Stryker (1996). (C,D) Ocular dominance histograms from mice (C) and cats (D) after alternating monocular deprivation. Data in C are from Gordon and Stryker (1996). Five mice were initially monocularly deprived for 5-6 days; daily alternating monocular deprivation was then performed for an additional 4-8 days. Neurons were recorded from the hemisphere contralat- eral to the initially deprived eye. Data in D are from Presson and Gordon (1979). Four kittens underwent daily alternating monocular deprivation for 21 days.

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VISUAL CORTICAL PLASTICITY IN CATS AND MICE

Cellular Mechanisms The cellular mechanisms underlying the correlation-based plasticity of the of Visual Cortical developing visual cortex have been explored primarily with Plasticity pharmacological techniques. Cortical infusion of tetrodotoxin, which blocks all neural activity, prevents the plasticity subsequent to monocular deprivation (Reiter et al. 1986). Infusion of the GABAA receptor agonist muscimol, which blocks only postsynaptic activity, reverses the direction of plasticity induced by lid suture. Inputs from the deprived eye, better correlated with the inactivated cortical cells, strengthen physiologically and expand anatomically (Reiter and Stryker 1988; Hata and Stryker 1994). These effects of muscimol demonstrate a role for the postsynaptic, cortical cell in determining the direction of ocular dominance plasticity, and confirm its Hebbian nature. Roles for various neurotransmitter systems in ocular dominance plasticity have been proposed. The N-methyl-n-aspartate (NMDA) receptor in particular was an early target of investigation, because its requirement for simultaneous presynaptic and postsynaptic activation makes it an ideal correlation detector (Collingridge and Bliss 1987; Mayer and Westbrook 1987). Cortical infusion of the NMDA receptor antagonist APV [D(-)-2-amino-5-phosphonovaleric acid] prevents the shifts in responsiveness induced by monocular deprivation in kittens (Kleinschmidt et al. 1987; Bear et al. 1990), although NMDA receptor activation appears to be required for visually evoked activity (Miller et al. 1989a; Bear et al. 1990). Other manipulations that diminish ocular dominance plasticity, such as interfering with modulatory neurotransmission, also have significant effects on cortical activity (Bear and Singer 1986; Gu and Singer 1993, 1995), leaving open the possibility that these systems are not specifically required for plasticity but rather generally facilitate depolarization of the cortical . Other manipulations, such as blockade of nitric oxide synthase (Reid et al. 1996; Ruthazer et al. 1996) or metabotropic glutamate receptors (Hensch and Stryker 1996), fail to prevent the effects of deprivation. More recently, a number of experiments have begun to support a role for in visual cortical plasticity (for recent review, see Thoenen 1995; Boenhoeffer 1996; Ghosh 1996). Injection of nerve growth factor (NGF) into the cerebral ventricles has been shown to prevent the physiological effects of monocular deprivation in and mice (Maffei et al. 1992; M. Fagiolini and M.P. Stryker, pers. comm.), although ventricular NGF has a much smaller effect in cats (Carmignoto et al. 1993). Cortical infusion of NGF appears not to block monocular deprivation effects in the cat (Galuske et al. 1996; D.C. Gillespie, M.C. Crair, and M.P. Stryker, pers. comm.). In contrast, infusion of -derived neurotrophic factor (BDNF), 4/5 (NT4/5), or trk-B/immunoglobulin chimeras into kitten visual cortex interferes with ocular dominance column formation and/or maintenance (Cabelli et al. 1995; R.J. Cabelli and C.J. Shatz, pets. comm.; D.C. Gillespie, M.C. Crair, and M.P. Stryker, pers. comm.), and cortical NT4/5 but not BDNF prevents the LGN cell shrinkage normally associated with monocular deprivation in ferrets (Riddle et al. 1995). A differential effect of NT4/5 and BDNF on dendritic growth in ferret cortical cultures has also been seen (McAllister et al. 1995). Interestingly, BDNF causes a muscimolqike reversal of the effects of monocular deprivation in cats, suggesting that BDNF is not acting as a straightforward growth signal (Galuske et al.

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1996). In addition to neurotrophins, proteases have been implicated in ocular dominance plasticity in recent preliminary reports (C.B. Griesinger and C.M. Mfiller, pers. comm.).

IN VITRO MODELS The paucity of direct evidence for cellular mediators of ocular dominance plasticity spurred attempts to develop in vitro models. In particular, long-term potentiation (LTP) and long-term depression (LTD) of synaptic efficacy in slices from visual cortex have been suggested to play a role in the changes seen in vivo (Artola and Singer 1987; Kandel and O'Dell 1992; Tsumoto 1992; Bear and Kirkwood 1993). These models share several properties with ocular dominance plasticity. High-frequency stimulation of inputs onto layer III pyramidal neurons results in depolarization of the cortical cell and strengthening of the stimulated (Artola and Singer 1987; Kirkwood et al. 1993). Low-frequency stimulation may result in synaptic strengthening or weakening depending on the level of postsynaptic depolarization, consistent with a correlation-based rule for synaptic efficacy changes (Artola et al. 1990; Kirkwood and Bear 1994a,b). At least some forms of LTP and LTD require NMDA receptor activation (Collingridge and Bliss 1987; Bear and Kirkwood 1993; Kirkwood et al. 1993). Interestingly, LTP induced by stimulation of the white matter cannot be obtained in adult animals without inhibitory neurotransmitter antagonists CKato et al. 1991; Kirkwood and Bear 1994a). This requirement for disinhibition begins at about the same time the critical period for ocular dominance plasticity ends. Furthermore, clark rearing, which prolongs the critical period, also prolongs the requirement for disinhibition (Mower 1991; Fox 1995; Kirkwood et al. 1995). Finally, LTP can be induced in thalamocortical inputs to layer IV of the somatosensory cortex; LTP induction in this system declines with an earlier time course, similar to that demonstrated for experience-dependent plasticity of somatosensory receptive fields (Crair and Malenka 1996). These data suggest a relationship between LTP and plasticity of the developing neocortex (Bear 1996). Although much is known about the cellular mechanisms underlying LTP and LTD, the relevance of this information for ocular dominance plasticity is questionable. Pharmacological and genetic dissection of visual cortical plasticity in vitro has suggested roles for calcium and calcium/calmodulin-dependent protein kinases in LTP (Kimura et al. 1990; Funauchi et al. 1992; Aroniadou et al. 1993; Kirkwood et al. 1997) and calcium and calcium/calmodulin-dependent protein phosphatases in LTD (Brocher et al. 1992; Komatsu and Iwakari 1992; Funauchi et al. 1994; Kirkwood and Bear, 1994b). Furthermore, by analogy to similar forms of plasticity studied in the hippocampus, roles for several other molecules and processes have been suggested (Tsumoto 1992). The list of potential mediators of plasticity derived from these in vitro models provides a wealth of suggestions for in vivo experiments. The expression of several of these molecules and processes changes in development with suggestive postnatal time courses, providing additional correlative evidence for a potential role in ocular dominance plasticity (Hashimoto et al. 1988; Dudek and Bear 1989; Burgin et al. 1990; Fox et al. 1992). Nonetheless, with the possible exception of the NMDA receptor, no direct links between plasticity in vitro and in vivo have yet been established.

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Evidence from Gene In general, increased understanding of the molecular mechanisms of visual Disruption cortical plasticity has been hampered by the need for specific, effective, Experiments in Mice and nontoxic pharmacological agents. Furthermore, it is generally difficult and often impossible to verify delivery and efficacy of a given drug, which is necessary for the proper interpretation of negative results and partial effects. The mouse model, although encumbered by its own caveats and difficulties (see below), circumvents these particular problems, as mice with verifiable and specific defects in any known gene can bc generated and tested in a straightforward manner. The study of visual cortical plasticity in mutant mice is in its infancy, yet it has already begun to lend insight into the cellular mechanisms underlying activity-dependent development. Mice with targeted disruptions in genes encoding the ~-isoform of protein kinase C, the C[31 catalytic and RI[3 regulatory subunits of cAMP-dependent protein kinase (PKA), or the neuronal surface protein Thy-1 have each been shown to have normal ocular dominance plasticity, ruling out an absolute requirement for these particular molecules (Gordon 1995; Gordon et al. 1996a,b; T.K. Hensch, J.A. Gordon, E.P. Brandon, G.S. McKnight, R.L. Idzerda, and M.P. Stryker, in prep). In addition, mice with a targeted disruption in the gene encoding the ~-isoform of calcium/ calmodulin-dependent protein kinase II (0~CaMKII) have a severe but variable deficit in ocular dominance plasticity, suggesting a role for calcium signaling via this protein (Gordon et al. 1996a). The experiments using ctCaMKII-deficient mice are reviewed briefly here.

c~CaMKII-DEFICIENT MICE; A A potential role for o~CaMKII in visual cortical plasticity is supported by a HINT AT MECHANISM number of lines of evidence. Neocortical expression of aCaMKII rises with a postnatal time course, and is altered by monocular deprivation (Hendry and Kennedy 1986; Kelly et al. 1987; Burgin 1990). Pharmacological experiments have implicated calcium/ calmodulin-dependent protein kinases in LTP studied by pairing whole-cell depolarization with afferent stimulation in both hippocampal and visual cortical slices (Malinow et al. 1989; Funauchi et al. 1992; Pettit et al. 1994; Lledoe et al. 1995). Mice lacking oLCaMKII were also found to have reduced visual cortical LTP when studied using field potentials and high-frequency afferent stimulation, although the reduction in critical period-aged mice was less marked than that in adult mice (Fig. 3A; Kirkwood et al. 1997). Visual cortical LTP has yet to be studied using whole-cell recording in ~CaMKII-deficient mice; both whole-cell and field potential LTP is disrupted in hippocampal slices from these mutants (Silva et al. 1992). A study of visual cortical plasticity in vivo in the c~CaMKII mutants revealed a variable deficit, demonstrating a role for the protein in ocular dominance plasticity (Gordon et al. 1996a). A paired analysis of monocularly deprived animals revealed that the txCaMKII mutants shifted on average less than identically deprived controls. Not all mutants shifted less, however. In an additional series of experiments, monocularly deprived mutants fell into two groups: Half the animals shifted to the same extent as controls, whereas the other half failed to do so (Fig. 3B). Interestingly, the animals with reduced plasticity nonetheless developed fully normal visual responses.

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Figure 3: Visual cortical plasticity in o~CaMKII-deficient mice. (A) Theta burst-in- duced LTP of field responses was reduced in mutant (open symbols) vs. wild-type (closed symbols) cortical slices. The reduction was greater for adult (circles) than critical period-aged (triangles) mice. Data are from Kirkwood et al. (1997). (B) Mon- ocular deprivation was greatly diminished in half of the oLCaMKII-deficient mice tested. Individual and mean bias indices for homozygous mutants (hatched bars; 9 and heterozygous and wild-type controls (open bars; A and ~, respectively) are shown. Data are from Gordon et al. (1996a).

Because these experiments were conducted blind to genotype using littermate controls, they constitute genetic proof of a role for oLCaMKII in ocular dominance plasticity. Why half the mice retained plasticity despite the lack of oLCaMKII has yet to be established, although there are several potential explanations. The animals studied were not genetically identical, allowing for the possibility that an independently segregating gene governs the requirement for the cxCaMKII molecule. Alternatively, biochemical compensation might be variably induced in the mutants. Regardless of the cause of the variability, there are many potential parallel mechanisms that might obviate the requirement for oLCaMKII, including other isoforms of calcium/calmodulin-dependent protein kinase, other calcium-responsive kinases, and other signal transduction systems; many of these are expressed in critical period visual cortex (Brandt et al. 1987; Huang et al. 1987, 1988; Cadd and McKnight 1989; Tsujino et al. 1990; Braun and Schulman 1995).

LIMITATIONS OF MOUSE As with any individual technique, significant caveats hamper the MODELS interpretation of results from genetically altered mice. The most important of these are the potential differences between activity-dependent plasticity

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in the mouse as compared with other species. Although the rules underlying visual cortical plasticity in the mouse appear identical to those in the cat (Gordon and Stryker 1996), it is possible that mechanistic differences exist between the two species. This troubling notion is raised by the difference between the effect of NGF in rodents and cats, although differences in the timing and route of administration may explain the discrepancy (Maffei et al. 1992; Carmignoto et al. 1993; Thoenen 1995; Galuske et al. 1996; D.C. Gillespie, M.C. Crair, and M.P. Stryker, pers. comm.; M. Fagiolini and M.P. Stryker, pers. comm.). Continued comparison of data from mice and cats eventually should determine the significance of interspecies differences between mice and higher animals. Even given a relevant mouse model, mice with targeted deletions propagated in the germ line raise additional concerns, as the protein of interest is lacking in all tissues and throughout development. Indirect effects of the induced mutation, such as developmental abnormalities or compensatory processes, cannot be ruled out. Furthermore, it may be difficult to define in which tissues the mutation exerts its effects. Tissue-specific and inducible gene targeting techniques have been developed to minimize these drawbacks (Tsien et al. 1996a; Wilson and Tonegawa 1997). These advances have already begun to clarify the role of aCaMKII in hippocampal-dependent learning (McHugh et al. 1996; Rotenberg et al. 1996; Tsien et al. 1996b). Until these tools become more widely used, however, one must take care in interpreting the results of gene knockout experiments.

Toward a Molecular Caveats notwithstanding, the combined approach of pharmacology in the Understanding of cat and rat models and, now, genetics in the mouse, has begun to identify Developmental likely key mediators of plasticity. With a little imagination, these individual Plasticity elements can be strung together into a model "plasticity pathway" (Fig. 4). According to this preliminary model, geniculocortical inputs trigger plasticity via glutamate-induced depolarization, which in turn causes an increase in intracellular calcium. The rise in calcium might be accomplished by activation of voltage-gated calcium channels, release from intracellular stores, or influx through opened NMDA receptors; there is no conclusive evidence as to which of these mechanisms are required (Miller et al. 1989a; Bear et al. 1990; Rauschecker 1991). Calcium activates oLCaMKII, and either calcium or depolarization activates some parallel pathway, both of which are likely involved in the resultant plasticity (Gordon et al. 1996a). Modulatory neurotransmitter systems and GABA-mediated inhibition probably affect plasticity by facilitating and inhibiting depolarization, respectively (Reiter and Stryker 1988; Bear and Singer 1986; Gu and Singer 1993, 1995; Hata and Stryker 1994). Neurotrophins might function as growth-promoting signals to geniculocortical afferents and cortical neurons (McAllister et al. 1995; Riddle et al. 1995; Boenhoeffer 1996; Cabelli et al. 1996; Ghosh 1996) and/or as facilitators of modulatory neurotransmission (Mafei et al. 1992; Thoenen 1995). Finally, proteases are likely required for geniculocortical afferent arbors to grow (C.B. Griesinger and C.M. Miiller, pers. comm.). Notice the many qualifying words in this description; the bulk of this model remains speculative. Much work needs to be done to prove or disprove each element. To this end, the mouse model of ocular dominance plasticity ofers some key advantages. Hypotheses regarding any particular molecule can

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Figure 4: Diagram of candidate plasticity pathway. Individual steps have been placed in this diagram only if direct tests of ocular dominance plasticity in vivo have demonstrated a role for the molecule or process. Arrows linking each step are solid where good evidence exists to support a relationship between the two steps; arrows are dashed where the relationship is not firmly established. References are given in the text. Modulatory and inhibitory inputs besides cholinergics are omitted for clar- ity. (5HT) Serotonin receptor; (NE) noradrenergic receptor; (ACh) acetylcholine re- ceptor; (Glu) glutamate; (tPA) tissue plasminogen activator.

be tested directly using specific mutants with known, induced mutations. Pharmacological interventions can be combined with genetic models to begin testing the interactions between elements. For instance, one could test whether neurotrophins are able to block the residual plasticity found in some oLCaMKII-deficient mice, and thereby attempt to order these mediators within the pathway. The ability to mate lines with different mutations permits a similar analysis to be conducted genetically; parallel pathways might also be discovered using animals with multiple mutations. In addition, the effects of a given mutation on physiology in vivo and in vitro may be compared, allowing tests of hypotheses derived from in vitro experiments; this approach is currently being taken to explore the relationship between various models of LTP and ocular dominance plasticity (Gordon et al. 1995; T.K. Hensch, J.A. Gordon, E.P. Brandon, R.L. Idzerda, G.S. McKnight, and M.P. Stryker, in prep.). Finally, with the characterization of barrel-field plasticity in normal and mutant animals, developmental plasticity in different neocortical areas may be compared directly (Fox 1992, 1994; Schlaggar et al. 1993). Already, differences in the requirement for aCaMKII have been demonstrated (Glazewski et al. 1996; Gordon et al. 1996a). Clearly, pharmacological and genetic techniques are complementary

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tools. Pharmacology allows one exquisite spatial and temporal control, but the adequacy of the intervention can be difficult to achieve and verify. Genetic intervention permits absolute and easily verifiable effects, but, as conventionally applied, at the expense of spatial and temporal specificity. Independently these two approaches have brought us to the brink of what will hopefully prove to be an explosion of understanding in the cellular mechanisms underlying developmental plasticity in the neocortex. Combining the two approaches should allow increasing control over the in vivo environment, helping us over that brink and leading us to a better understanding of how cats and mice, and all of us, learn to see.

Acknowledgments I thank Drs. Michael Stryker and Takao Hensch for their careful reading of and critical comments on this manuscript, and Sharif Taha, Deda Gillespie, and Michael Silver for helpful discussions. Much of the work described here was carried out in the laboratory of Dr. Stryker, with the support of the National Institutes of Health and the Frontiers Science Program.

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Cellular mechanisms of visual cortical plasticity: a game of cat and mouse.

J A Gordon

Learn. Mem. 1997, 4: Access the most recent version at doi:10.1101/lm.4.3.245

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