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Cellular Mechanisms of Visual Cortical Plasticity: a Game of Cat and Mouse

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Cellular Mechanisms of Visual Cortical Plasticity: a Game of Cat and Mouse Downloaded from learnmem.cshlp.org on October 3, 2021 - Published by Cold Spring Harbor Laboratory Press REVIEW Joshua A. Gordon 1 Cellular Mechanisms of Visual Department of Physiology Cortical Plasticity: A Game of Cat 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 visual system 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 visual cortex of cats and monkeys, where initially overlapping inputs from the two eyes segregate into ocular dominance columns during a critical period (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 mammals, developmental plasticity 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 L E A R N / N G & M E M O 245 Downloaded from learnmem.cshlp.org on October 3, 2021 - Published by Cold Spring Harbor Laboratory Press Gordon 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 ocular dominance column segregation appears to be the correlation between inputs from one eye 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 neurons (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 monocular deprivation 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 cell. 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 L E A R N / N G & M E M O R Y 246 Downloaded from learnmem.cshlp.org on October 3, 2021 - Published by Cold Spring Harbor Laboratory Press 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 species. Only the frontal 30-40 ~ of the upper portion of each visual hemifield is seen by the retinas of both eyes (Dfiiger 1975; Wagor et al. 1980). Retinal ganglion cell axons 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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