Ординатура / Офтальмология / Английские материалы / Eye, Retina, and Visual System of the Mouse_Chalupa, Williams_2008

synaptic events responsible for generating the VEP waveform (Mitzdorf, 1985). A recording electrode was tracked radially through primary visual cortex (V1) in 100 μm steps from the pial surface to below the white matter. After each 100 μm advancement of the electrode, at least 200 VEPs were collected in response to a binocularly presented highcontrast sinusoidal grating (0.05 c/deg), pattern reversing at 1 Hz. A representative example of the average VEP recorded at each depth is presented in the left column of figure 38.1C. VEP waveforms recorded through the depth of the cortex were typically composed of an initial negativity followed by a more variable positivity. These components correspond roughly to those described in the primate (Schroeder et al., 1991). The VEP waveform with the maximum negativity and shortest latency was recorded at a depth corresponding to layer 4 (ca. 450 μm ventral from the pial surface). Based on CSD analyses performed in juvenile and adult mice, recording electrodes were implanted in V1 at a site yielding maximum binocular responsiveness and at a depth yielding the maximum negative-going VEP (figure 38.1B), which reflects a synaptic current sink in layer 4 (Huang et al., 1999; Sawtell et al., 2003), likely resulting from activity in thalamocortical inputs to this layer (see figure 38.1C, middle and right column).

OD refers to the relative contribution of the two eyes to visually evoked responses in visual cortex. It is well known from both single-unit and VEP recordings that in mice, there is a substantial bias toward the contralateral eye (Gordon and Stryker, 1996; Hanover et al., 1999; Huang et al., 1999). In the awake mouse preparation, the VEP elicited by contralateral eye stimulation is normally about two to three times greater than that elicited by ipsilateral eye stimulation (figure 38.1D and E). To assess the stability of the extended duration recording preparation, we tracked changes in this ratio and the absolute VEP amplitude over time in normally reared mice. Under conditions of normal visual experience, the amplitude of the responses evoked by the two eyes and their ratio remained stable for many days (see figure 38.1E).

Effects of monocular deprivation in juvenile mice

VEP responses are altered substantially if the contralateral eyelid is sutured (figure 38.2A). Although 1 day of MD causes variable changes in OD (figure 38.2A2), 3 days of MD reliably causes a substantial and significant depression of deprived-eye VEPs (solid bars in figure 38.2A3). Interestingly, nondeprived (ipsilateral)-eye VEPs remained unchanged after 3 days of MD (open bars in figure 38.2A3) but were potentiated after a longer period of MD (open bars in figure 38.2A4 to A5). Thus, the OD shift observed following MD is initially accounted for entirely by rapid deprivation-induced response depression (figure 38.2A6). With longer periods of

MD, there is a compensatory increase in the response to stimulation of the nondeprived eye (figure 38.2A7). Had we analyzed contralateral/ipsilateral ratios only, we would not have been able to discern these phases of the OD shift, since the contralateral/ipsilateral ratio is the same after 3 days of MD as it is after 7 days of MD.

This bidirectional plasticity is also reflected in experiments in which binocular VEPs are collected from both hemispheres before and after MD of varying duration (figure 38.3). The VEPs in both hemispheres are equivalent in amplitude before MD (day 0 in figure 38.3B). However, after 3 days of MD, there is a dramatic drop in binocular VEP amplitude in the hemisphere contralateral to the deprived eye, reflecting massive synaptic weakening of the dominant input to this hemisphere. Such interhemispheric asymmetry is no longer observed after longer periods of MD (5 days), however. Early depression of deprived (contralateral)-eye responses can account for decreases in binocular VEPs at 3 days, and late potentiation of the open-eye response can explain the “renormalization” of binocular VEPs after 5 days of MD.

Mechanisms of the ocular dominance shift in mice

The synaptic mechanisms for cortical plasticity still remain largely unknown. A common hypothesis is that Hebbian synaptic plasticity, which is implemented in vivo by longterm potentiation (LTP) and long-term depression (LTD), drives rapid components of map plasticity (Malenka and Bear, 2004), whereas a slower anatomical rearrangement of synapses drives later components (Antonini and Stryker, 1996, 1998).

Our experiments show that MD in mice during the preadolescent critical period causes (1) rapid, deprivationinduced response depression and (2) delayed, deprivationenabled response potentiation. These two responses to MD are mechanistically distinct because they are affected differently by reducing activity in the deprived eye. Depression of deprived-eye responses is eliminated by intraocular injection of tetrodotoxin (TTX), suggesting that this early response to lid closure is triggered by activity originating in the deprived retina (Frenkel and Bear, 2004). On the other hand, potentiation of nondeprived ipsilateral eye responses is promoted by inactivation of the dominant contralateral eye, suggesting that this response to MD is enabled by reducing postsynaptic activity in visual cortex.

Some insight into the mechanisms of the early, depriva- tion-induced response depression have come from recent studies performed in rats. However, these studies have also revealed some important species-specific differences: (1) the OD shift in rats occurs more rapidly than in mice (after only 1 day of MD; Heynen et al., 2003), and (2) unlike in mice (see figure 38.2B) and kittens (Sherman and Wilson, 1975),

Figure 38.2 Effects of MD on visual cortical responsiveness. A1, Schematic diagram of visual information flow from the retina to the cortex. A recording electrode is implanted in the binocular zone of V1. A2–A5, Effects of 1, 3, 5, and 7 days of MD on contralateral and ipsilateral eye responses. A6 and A7, Summary of data shown in A2 to A5. Deprived-eye responses (A6, black symbols) decrease significantly after 3 days of monocular deprivation (A3) and stay

there is a substantial effect of deprivation on responses in the monocular segment of visual cortex, where there is no substrate for binocular competition (Sherman and Wilson, 1975). With these caveats in mind, we briefly review what the rat studies have revealed about potential mechanisms.

depressed during longer MD periods (A4 to A5). Open-eye responses (A7, open symbols) increase after 5 days of MD (A4) and reach statistical significance following 7 days of MD (A5). Gray symbols in both panels represent VEP responses obtained on day 0. B1 and B2, A brief period of MD that is sufficient to maximally depress responses in the binocular zone has no effect on VEP amplitude in the monocular segment of Oc1.

It is well established that at many excitatory synapses in the brain, weak activation of postsynaptic NMDA receptor can induce long-term synaptic depression (Malenka and Bear, 2004). Although the mechanisms vary, depending on location, there is good evidence both in visual cortex and in

Figure 38.3 Three days of MD result in an interhemispheric asymmetry of binocularly elicited VEPs. A, Recording electrodes were implanted bilaterally in the binocular zone of V1. B, VEPs in response to binocular visual stimulation are identical in amplitude in both hemispheres prior to MD (day 0, B1 to B3). B2, After 3 days of MD, however, binocular VEPs in the hemisphere contralateral

hippocampus that a prominent form of LTD is mediated by the modification and removal of postsynaptic AMPA receptors. Heynen et al. tested the hypothesis that MD in rats induces synaptic depression by the same mechanism as LTD. They showed in rats that monocular lid closure for 24 hours precisely mimics LTD with respect to altered AMPA receptor phosphorylation and decreased surface expression, and that synaptic depression by MD occludes LTD in slices of visual cortex. Moreover, these effects of MD failed to occur if NMDA receptors were blocked or if TTX was injected into the deprived eye. These data provide very strong evidence that MD induces LTD in rat visual cortex (McAllister and Usrey, 2003). Moreover, induction of LTD in visual cortex by electrical stimulation of the LGN caused a depression of VEPs indistinguishable from that caused by MD (Heynen et al., 2003).

A second “noncompetitive” mechanism for response depression in rat visual cortex involves changes in inhibition. Compelling evidence was recently provided that MD induces LTP of inhibitory connections from fast-spiking basket cells onto layer 4 pyramidal neurons in the monocular segment of rat Oc1 (Maffei et al., 2006). This mechanism likely contributes significantly to the depression of VEPs that has been observed in the monocular segment of rats after MD

to the deprived eye are significantly depressed, which is accounted for by the deprivation-induced depression of the deprived-eye responses. This binocular response depression is not observed after 1 day of MD (B1) or after a longer period of MD (B3) due to the delayed potentiation of open-eye responses.

(Heynen et al., 2003). However, it remains to be determined if the same changes occur in the binocular segment. Further, these findings may not apply to mice or cats, since the monocular segment responses are not affected by deprivation in the absence of binocular competition (see figure 38.2B).

Although the question of whether the strengthening of inhibition is a basis for response depression in the mouse remains open, there is some evidence that mechanisms of LTD do contribute. However, a recent study of LTD in mouse visual cortex revealed unexpected mechanistic divergence downstream from NMDA receptor activation, depending on the layer. Whereas layer 4 LTD appears to be identical to that observed in area CA1 of the hippocampus, and clearly involves AMPA receptor endocytosis, layer 3 LTD appears to involve a different mechanism that requires endocannabinoid signaling (Crozier et al., 2007). Both types of LTD were occluded by 3 days of MD in vivo, suggesting that both mechanisms can account for response depression in mouse visual cortex. However, the relative extent to which these mechanisms are responsible for the depression of VEPs remains to be determined.

With longer periods of MD, we observe potentiation of responses to the nondeprived eye. The fact that some recovery of deprived-eye responses also occurs at these time points

raises the possibility that this potentiation reflects a homeostatic scaling of VEPs following a period of relative cortical inactivity. However, arguing against scaling as an explanation is our finding that binocular deprivation fails to change VEP amplitude. We favor the hypothesis that reducing cortical activity by closing the contralateral eyelid causes a change in the threshold level of activation required to potentiate the nondeprived-eye synapses. This hypothesis is supported by the fact that open-eye potentiation is accelerated when the contralateral eye is inactivated with TTX (Frenkel and Bear, 2004).

The functional significance of electrophysiological findings in deprivation experiments can only be determined by performing behavioral studies. A considerable amount of research has been done to show the functional consequences of MD on deprived-eye acuity using various behavioral assays (Dews and Wiesel, 1970; Mitchell and MacKinnon, 2002). For many years, however, little attention was paid to determining the effects of MD on open-eye acuity. A recent study from our laboratory, utilizing a method developed to assess rodent visual acuity (Prusky and Douglas, 2003), documented an enhancement of acuity in the nondeprived eye of long-term MD rats (Iny et al., 2006). Although it remains to be shown whether the same is true in mice, a new study using a virtual optokinetic system showed a different form of interocular plasticity in adult mice, in which MD leads to an enhancement of the optokinetic response selectively through the nondeprived eye (Prusky et al., 2006).

A well-known mechanism for synaptic potentiation is revealed by the study of LTP. In the hippocampus, where it has been studied most extensively, LTP is associated with the delivery of AMPA receptors to synapses. Delivery of AMPA receptors following strong NMDA receptor activation requires molecular interactions with the long carboxy tails of AMPA receptor subunits, particularly GluR1. Viral overexpression of the C-terminal domain of GluR1 (GluR1-CT) competes with this interaction and blocks LTP (Malinow et al., 2000). LTP with properties similar to those observed in CA1 in hippocampus can also be elicited in visual cortex both in vivo and in vitro (Heynen and Bear, 2001; Kirkwood and Bear, 1994). Consistent with the notion that conserved mechanisms of LTP might be important for cortical plasticity, recent work in barrel cortex showed that GluR1-containing AMPA receptors are delivered to synapses in response to sensory stimulation, and this response was also blocked by overexpression of GluR1-CT (Takahashi et al., 2003). Furthermore, it is now well established that, like the threshold for naturally occurring response potentiation, the LTP threshold is lowered by a period of cortical inactivity (Kirkwood et al., 1996; Philpot et al., 2003).

LTP of potentials evoked by external sensory stimuli has been demonstrated in vivo in the visual cortex of rats

(Heynen and Bear, 2001). In that study, the potentiating stimulus was electrical stimulation of the thalamocortical pathway, which resulted in an enhancement of visual potentials evoked by natural visual stimuli. Repetitive noninvasive visual sensory stimulation has also been shown to result in LTP-like enhancements in the visual system of the developing tadpole. Using in vivo whole-cell recordings from the tectum of Xenopus tadpoles, Zhang et al. (2000) showed that repetitive dimming-light stimulation (0.3 Hz) applied to the contralateral eye resulted in persistent enhancement of glutamatergic inputs. Recently, Teyler et al. observed LTP in the visual cortex of adult humans by measuring the amplitude of event-related potentials recorded from the scalp before and after a visual conditioning protocol (checkerboard stimulation presented at an average rate of approximately 1 Hz) (Clapp et al., 2006; Teyler et al., 2005).

Thus, there is much indirect support for the general notion that deprivation-enabled potentiation of the open-eye response uses the mechanisms of LTP. How is this modulated by the history of cortical activity? A hypothesis for which there is considerable evidence is that the LTP threshold is set by the number and type of NMDA receptors, which in turn are modified by deprivation. Specifically, it has been shown in both rats and mice that the period of deprivation required to lower the LTP threshold also changes the ratio of NR2A and NR2B subunits in native NMDA receptors (Chen and Bear, 2007; Quinlan et al., 1999). The switch from 2A to 2B lowers the LTP threshold (Barria and Malinow, 2005), and, we speculate, this change enables potentiation of open-eye responses.

Stimulus-selective response potentiation

Although it seems clear that neural activity is necessary for the development of appropriate brain circuits, it is less clear whether it simply allows predetermined growth to move forward or whether it plays an instructive role in determining brain circuitry. One of the classic paradigms for studying whether activity plays a permissive or an instructive role in shaping cortical responses is stripe rearing, or rearing an animal in an environment where only a single orientation is present (Blakemore and Cooper, 1970; Hirsch and Spinelli, 1970). In this situation, a permissive role for activity would imply that, from a starting point where roughly equal numbers of neurons respond to all possible orientations, only those receiving adequate stimulation from the environment will survive and mature, while others will lose responsiveness and may eventually disappear. An instructive role for activity would mean that previously nonselective cells acquire a preference for the orientation present in the environment, or that cells shift their orientation preference toward the experienced orientation, while maintaining normal responsiveness. In other words, a cell’s RF would change.

In both juvenile and adult mice we discovered that repeated daily exposure to a sinusoidal grating stimulus of a particular orientation, pattern reversing at 1 Hz, resulted in a gradual and saturable increase in VEP amplitude that was specific to that orientation (Frenkel et al., 2006). Once daily exposure to 200 stimuli gradually increased the response, which saturated after 5 days of exposure (figure 38.4A). We tested various parameters to characterize this stimulusselective response potentiation (SRP). Varying the number of stimuli per session, the intersession interval, and the temporal frequency of visual stimulation did not result in a significant change in SRP expression. Varying the contrast, however, did have an effect on SRP expression: at low stimulus contrast, SRP did not occur. A consolidation period was required for SRP expression, as it does not occur within a single recording session. Interestingly, we failed to observe interocular transfer of SRP (figure 38.4B). This finding,

Figure 38.4 Characterization of stimulus-selective response potentiation (SRP). A, Brief daily exposure to a grating stimulus of a single orientation selectively potentiates the amplitude of VEPs to stimuli of that orientation. VEP amplitude elicited during ipsilateral eye (open symbols), contralateral eye (gray symbols), and binocular (black symbols) viewing conditions increase in response to visual stimuli of a single orientation until it reaches saturation after 4 days of exposure. When stimuli of a novel orientation are also presented on day 4, the amplitude of this new orientation is comparable to the preexposed orientation on day 0. B, SRP is eye-specific. SRP elicited to presentations of stimuli of orientation X° to the ipsilateral eye (open circles) is not accompanied by SRP in the contralateral eye (solid circle). Squares indicate VEPs in response to X + 90°; circles indicate VEPs in response to X°. VEP amplitudes are normalized to the ipsilateral response elicited on day 1.

along with the fact that specific cortical manipulations of NMDA and AMPA receptors disrupt SRP, strongly suggests that SRP reflects modification of excitatory LGN synapses in layer 4.

Since LTP is a leading model for experience-dependent plasticity as well as for some forms of learning (Rioult-Pedotti et al., 1998, 2000; Whitlock et al., 2006), we hypothesized that SRP and LTP may share common mechanisms. We successfully tested and confirmed this hypothesis by demonstrating that blocking NMDA receptors both pharmacologically and genetically, and disrupting AMPA receptor trafficking, prevents SRP expression. We believe that LTP-like synaptic strengthening is an underlying mechanism for SRP.

Our data reveal a novel form of experience-dependent plasticity in mouse visual cortex. This form of plasticity is not restricted to an early developmental age, as it occurs in animals well beyond the classically defined critical period (P33). SRP is a rapidly induced and robust phenomenon. Moreover, once the response to the experienced orientation increases, the VEP amplitudes remain elevated despite several days in which no testing is performed. This suggests that the mechanisms of SRP may contribute to certain forms of perceptual learning. Based on properties observed in humans, Karni and Sagi (1991) suggested a reductionist model for perceptual learning, involving Hebbian increases in synaptic strength in V1 that require a consolidation period to become manifest. The leading experimental paradigm for Hebbian modifications is LTP, and the key properties of LTP nicely match those of SRP, including input specificity, cooperativity, and persistence. Moreover, at many cortical synapses, induction of LTP requires strong activation of NMDA receptors, and expression of LTP requires the delivery of AMPA receptors. Our experiments reveal that SRP shares identical molecular requirements.

In light of these findings it is especially important to consider that the diverse effects of sensory experience in shaping the nervous system may be mediated by a diversity of cellular and molecular mechanisms. Of particular interest are changes in neural activity that reflect particular qualities of sensory experience. Such changes are likely to be involved in perceptual learning in adults (Ghose, 2004) and may also occur as a result of selective experience during development (Movshon and Van Sluyters, 1981). Little is known regarding the mechanisms underlying such stimulus-specific changes in cortical responses. Our SRP findings lend further support to the idea that diverse effects of sensory experience in shaping the brain may be mediated by common elementary mechanisms of synaptic plasticity.

Adult ocular dominance plasticity

The idea that primary sensory cortex remains plastic beyond the traditionally defined critical period is quite new. It was

long assumed that cells in V1 had fixed properties, passing along the product of a stereotyped operation to the next stage in the visual pathway. Any plasticity dependent on visual experience was thought to be restricted to a critical period. It has become clear, however, that the critical period applies to a limited set of properties and connections, each property being subject to its own critical period. Other properties remain mutable throughout life. Therefore, it is very important to study adult cortical plasticity, since it may underlie perceptual learning and participate in recovery of function after brain injury.

Recent evidence suggests that most critical periods do not close abruptly and absolutely but gradually and often incompletely. For example, the capacity for rapid plasticity in somatosensory (S1) cortex declines sharply in some cortical layers soon after birth, but persists in other layers into adulthood (Diamond et al., 1994; Glazewski and Fox, 1996), and a similar pattern has been observed for OD plasticity in some species (Daw et al., 1992). Correspondingly, sensory deprivation or behavioral training can induce substantial plasticity even in adults (Buonomano and Merzenich, 1998; Hofer et al., 2006a; Karmarkar and Dan, 2006; Shuler and Bear, 2006). Whether critical period plasticity and adult plasticity share common cellular and molecular mechanisms is unclear.

Our understanding of visual plasticity in the adult mouse was previously based primarily on single-unit extracellular recordings from cortical neurons, in which the relative balance of inputs representing each eye is assessed within the binocular zone. These studies suggested that brief periods (3–4 days) of MD cause OD plasticity only within a welldefined critical period ending at P35 (Gordon and Stryker, 1996). We reexamined the critical period for OD plasticity in the mouse, initially using an anesthetized preparation, and were surprised to find that 5 days of MD shifted OD in adult mice—a time well beyond the classically defined critical period. The basis for this remarkable adult plasticity was further studied by daily VEP recordings using chronically implanted electrodes in awake animals, which allowed OD and the strength of right eye and left eye inputs to be tracked over time at the same sites. As in anesthetized mice, 5 days of adult MD caused a large OD shift in the hemisphere contralateral to the deprived eye, whereas 3 days of adult MD elicited no significant plasticity. Our data suggested that the adult OD shift was due almost exclusively to an increase in absolute amplitude of ipsilateral (open) eye VEPs rather than to a decrease in the amplitude of contralateral (closed) eye VEPs. Our interpretation was that adult OD plasticity was due to the active strengthening of initially weak ipsilateral inputs in response to closure of the contralateral, dominant eye. Strengthening of ipsilateral inputs developed gradually over the first 3–6 days of MD, explaining why briefer periods of MD failed to elicit OD changes in adult

mice. In our study (Sawtell et al., 2003), we demonstrated for the first time that OD plasticity occurs in adult mice, and suggested that it uses different mechanisms than plasticity observed during the classically defined critical period.

This original study (Sawtell et al., 2003) was performed prior to our discovery of SRP, and in these experiments, stimuli of the same orientation were used across multiple days of testing. In the light of our recent discovery of SRP (Frenkel et al., 2006), we reconsidered our prior interpretation of OD plasticity in the adult mouse. In those experiments, the manifestation of deprived-eye weakening could have been easily masked by naturally occurring experiencedependent strengthening of visual responsiveness (SRP). Since we were likely inducing SRP, the experience-de- pendent strengthening that occurred as a result of baseline VEP measurements may have obscured deprivation-induced weakening of the deprived eye (Sawtell et al., 2003). When we redesigned the experimental protocol to minimize the recording session time and avoided any prolonged patterned visual stimulation with stimuli of the same orientation, we were able to unmask a depression of the deprived-eye response after 7 days of MD (figure 38.5A2). Thus, the visual cortex of the adult mouse is not immune to synaptic weakening. In fact, the only difference we are able to detect between juvenile and adult OD plasticity is the time scale of the shift: there is no OD shift after 3 days of MD in adult mice (figure 38.5A1), whereas in juveniles the same manipulation results in a very dramatic shift in juvenile animals (see figure 38.5B1).

Other laboratories have recently confirmed that rapid experience-dependent plasticity exists in the mature V1 of mice using a variety of measures, including single-unit recordings (Hofer et al., 2006b; Pham et al., 2004; Tagawa et al., 2005). Thus, the finding of adult OD plasticity is robust to assays of input strength (e.g., VEPs in layer 4) and postsynaptic spiking (e.g., single units in all layers). So the question arises: does a mouse have a critical period? Or, put slightly differently, is the mouse a good experimental model in which to study the critical period for OD plasticity? Many laboratories have devoted their resources to studies of the mechanisms underlying the opening and closure of the critical period (Hensch, 2004) and, despite recent findings, it may be premature to dismiss the mouse as a species of choice for studying this question. Nonetheless, it is abundantly clear that the mouse visual cortex is capable of OD plasticity both during early postnatal development and in adulthood, and that many experiments need to be reevaluated in this light. Uncovering the underlying cellular and molecular mechanisms of OD plasticity will require additional experiments that take into account not only age and the length of MD but also laminar and spatial location within the cortex.

Figure 38.5 Juvenile form of OD plasticity is observed in adult mice following longer periods of MD. A1 to A2, Effects of 3 and 7 days of MD on OD plasticity in adult mice (P60). B1 to B2, Effects of 3 and 7 days of MD on OD plasticity in juvenile mice (P28). Three days of MD had no effect on deprivedand nondeprived-eye

acknowledgments Work was supported by grants from the National Eye Institute, the National Institute for Mental Health, and the Howard Hughes Medical Institute. We thank Dr. Arnold Heynen for his valuable comments and help with this chapter.

REFERENCES

Adams, D. L., and Horton, J. C. (2003). Capricious expression of cortical columns in the primate brain. Nat. Neurosci. 6:113– 114.

Antonini, A., and Stryker, M. P. (1996). Plasticity of geniculocortical afferents following brief or prolonged monocular occlusion in the cat. J. Comp. Neurol. 369:64–82.

Antonini, A., and Stryker, M. P. (1998). Effect of sensory disuse on geniculate afferents to cat visual cortex. Vis. Neurosci. 15:401–409.

Barria, A., and Malinow, R. (2005). NMDA receptor subunit composition controls synaptic plasticity by regulating binding to CaMKII. Neuron 48:289–301.

Blakemore, C., and Cooper, G. F. (1970). Development of the brain depends on the visual environment. Nature 228:477–478.

Buonomano, D. V., and Merzenich, M. M. (1998). Cortical plasticity: From synapses to maps. Annu. Rev. Neurosci. 21:149– 186.

Chen, W. S., and Bear, M. F. (2007). Activity-dependent regulation of NR2B translation contributes to metaplasticity in mouse visual cortex. Neuropharmacology 52(1):200–214.

Clapp, W. C., Eckert, M. J., Teyler, T. J., and Abraham, W. C. (2006). Rapid visual stimulation induces N-methyl-d-aspartate receptor-dependent sensory long-term potentiation in the rat cortex. Neuroreport 17:511–515.

VEP amplitude in adult mice (A1), whereas it resulted in a dramatic shift in juvenile mice (B1). Longer periods of MD shift ocular dominance in adult mice (A2). Open-eye responses increase and deprivedeye responses depress following MD. The shift after 7 days of MD is quantitatively the same as in juvenile mice (B2).

Crozier, R. A., Wang, Y., Liu, C.-H., and Bear, M. F. (2007). Deprivation-induced synaptic depression via distinct mechanisms in different layers of mouse visual cortex. Proc. Natl. Acad. Sci. U.S.A. 104(4):1383–1388.

Daw, N. W., Fox, K., Sato, H., and Czepita, D. (1992). Critical period for monocular deprivation in the cat visual cortex. J. Neurophysiol. 67:197–202.

Dews, P. B., and Wiesel, T. N. (1970). Consequences of monocular deprivation on visual behaviour in kittens. J. Physiol. 206:437– 455.

Diamond, M. E., Huang, W., and Ebner, F. F. (1994). Laminar comparison of somatosensory cortical plasticity. Science 265: 1885–1888.

Dräger, U. C. (1978). Observations on monocular deprivation in mice. J. Neurophysiol. 41:28–42.

Emerson, V. F., Chalupa, L. M., Thompson, I. D., and Talbot, R. J. (1982). Behavioural, physiological, and anatomical consequences of monocular deprivation in the golden hamster (Mesocricetus auratus). Exp. Brain Res. 45(1–2):168–178.

Frenkel, M. Y., and Bear, M. F. (2004). How monocular deprivation shifts ocular dominance in visual cortex of young mice. Neuron 44:917–923.

Frenkel, M. Y., Sawtell, N. B., Diogo, A. C., Yoon, B., Neve, R. L., and Bear, M. F. (2006). Instructive effect of visual experience in mouse visual cortex. Neuron 51:339–349.

Ghose, G. M. (2004). Learning in mammalian sensory cortex. Curr. Opin. Neurobiol. 14:513–518.

Glazewski, S., and Fox, K. (1996). Time course of experiencedependent synaptic potentiation and depression in barrel cortex of adolescent rats. J. Neurophysiol. 75:1714–1729.

Gordon, J. A., and Stryker, M. P. (1996). Experience-dependent plasticity of binocular responses in the primary visual cortex of the mouse. J. Neurosci. 16:3274–3286.

Hanover, J. L., Huang, Z. J., Tonegawa, S., and Stryker, M. P. (1999). Brain-derived neurotrophic factor overexpression induces precocious critical period in mouse visual cortex. J. Neurosci. 19: RC40.

Hensch, T. K. (2004). Critical period regulation. Annu. Rev. Neurosci. 27:549–579.

Heynen, A. J., and Bear, M. F. (2001). Long-term potentiation of thalamocortical transmission in the adult visual cortex in vivo. J. Neurosci. 21:9801–9813.

Heynen, A. J., Yoon, B. J., Liu, C. H., Chung, H. J., Huganir, R. L., and Bear, M. F. (2003). Molecular mechanism for loss of visual cortical responsiveness following brief monocular deprivation. Nat. Neurosci. 6:854–862.

Hirsch, H. V., and Spinelli, D. N. (1970). Visual experience modifies distribution of horizontally and vertically oriented receptive fields in cats. Science 168:869–871.

Hofer, S. B., Mrsic-Flogel, T. D., Bonhoeffer, T., and Hübener, M. (2006a). Lifelong learning: Ocular dominance plasticity in mouse visual cortex. Curr. Opin. Neurobiol. 16:451–459.

Hofer, S. B., Mrsic-Flogel, T. D., Bonhoeffer, T., and Hübener, M. (2006b). Prior experience enhances plasticity in adult visual cortex. Nat. Neurosci. 9:127–132.

Horton, J. C., and Adams, D. L. (2005). The cortical column: A structure without a function. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 360:837–862.

Huang, Z. J., Kirkwood, A., Pizzorusso, T., Porciatti, V., Morales, B., Bear, M. F., Maffei, L., and Tonegawa, S. (1999). BDNF regulates the maturation of inhibition and the critical period of plasticity in mouse visual cortex. Cell 98: 739–755.

Hübel, D. H., and Wiesel, T. N. (1970). The period of susceptibility to the physiological effects of unilateral eye closure in kittens. J. Physiol. 206:419–436.

Iny, K., Heynen, A. J., Sklar, E., and Bear, M. F. (2006). Bidirectional modifications of visual acuity induced by monocular deprivation in juvenile and adult rats. J. Neurosci. 26:7368– 7374.

Issa, N. P., Trachtenberg, J. T., Chapman, B., Zahs, K. R., and Stryker, M. P. (1999). The critical period for ocular dominance plasticity in the ferret’s visual cortex. J. Neurosci. 19:6965– 6978.

Karmarkar, U. R., and Dan, Y. (2006). Experience-dependent plasticity in adult visual cortex. Neuron 52:577–585.

Karni, A., and Sagi, D. (1991). Where practice makes perfect in texture discrimination: Evidence for primary visual cortex plasticity. Proc. Natl. Acad. Sci. U.S.A. 88:4966–4970.

Kirkwood, A., and Bear, M. F. (1994). Hebbian synapses in visual cortex. J. Neurosci. 14:1634–1645.

Kirkwood, A., Rioult, M. C., and Bear, M. F. (1996). Experi- ence-dependent modification of synaptic plasticity in visual cortex. Nature 381:526–528.

Logothetis, N. K. (2003). The underpinnings of the BOLD functional magnetic resonance imaging signal. J. Neurosci. 23: 3963–3971.

Maffei, A., Nataraj, K., Nelson, S. B., and Turrigiano, G. G. (2006). Potentiation of cortical inhibition by visual deprivation. Nature 443:81–84.

Maffei, L., Berardi, N., Domenici, L., Parisi, V., and Pizzorusso, T. (1992). Nerve growth factor (NGF) prevents the shift in ocular dominance distribution of visual cortical neurons in monocularly deprived rats. J. Neurosci. 12:4651–4662.

Malenka, R. C., and Bear, M. F. (2004). LTP and LTD: An embarrassment of riches. Neuron 44:5–21.

Malinow, R., Mainen, Z. F., and Hayashi, Y. (2000). LTP mechanisms: From silence to four-lane traffic. Curr. Opin. Neurobiol. 10:352–357.

McAllister, A. K., and Usrey, W. M. (2003). Depressed from deprivation? Look to the molecules. Nat. Neurosci. 6:787–788.

Mitchell, D. E., and MacKinnon, S. (2002). The present and potential impact of research on animal models for clinical treatment of stimulus deprivation amblyopia. Clin. Exp. Optom. 85: 5–18.

Mitzdorf, U. (1985). Current source-density method and application in cat cerebral cortex: Investigation of evoked potentials and EEG phenomena. Physiol. Rev. 65:37–100.

Movshon, J. A., and Van Sluyters, R. C. (1981). Visual neural development. Annu. Rev. Psychol. 32:477–522.

Murphy, W. J., Pevzner, P. A., and O’Brien, S. J. (2004). Mammalian phylogenomics comes of age. Trends. Genet. 20:631–639.

Pham, T. A., Graham, S. J., Suzuki, S., Barco, A., Kandel, E. R., Gordon, B., and Lickey, M. E. (2004). A semi-persistent adult ocular dominance plasticity in visual cortex is stabilized by activated CREB. Learn. Mem. 11:738–747.

Philpot, B. D., Espinosa, J. S., and Bear, M. F. (2003). Evidence for altered NMDA receptor function as a basis for metaplasticity in visual cortex. J. Neurosci. 23:5583–5588.

Pizzorusso, T., Fagiolini, M., Porciatti, V., and Maffei, L. (1997). Temporal aspects of contrast visual evoked potentials in the pigmented rat: Effect of dark rearing. Vision. Res. 37:389– 395.

Porciatti, V., Pizzorusso, T., and Maffei, L. (1999). The visual physiology of the wild-type mouse determined with pattern VEPs. Vision. Res. 39:3071–3081.

Prusky, G. T., Alam, N. M., and Douglas, R. M. (2006). Enhancement of vision by monocular deprivation in adult mice. J. Neurosci. 26:11554–11561.

Prusky, G. T., and Douglas, R. M. (2003). Developmental plasticity of mouse visual acuity. Eur. J. Neurosci. 17:167–173.

Quinlan, E. M., Olstein, D. H., and Bear, M. F. (1999). Bidirectional, experience-dependent regulation of N-methyl-d-aspartate receptor subunit composition in the rat visual cortex during postnatal development. Proc. Natl. Acad. Sci. U.S.A. 96:12876– 12880.

Rioult-Pedotti, M. S., Friedman, D., and Donoghue, J. P. (2000). Learning-induced LTP in neocortex. Science 290:533–536.

Rioult-Pedotti, M. S., Friedman, D., Hess, G., and Donoghue, J. P. (1998). Strengthening of horizontal cortical connections following skill learning. Nat. Neurosci. 1:230–234.

Sawtell, N. B., Frenkel, M. Y., Philpot, B. D., Nakazawa, K., Tonegawa, S., and Bear, M. F. (2003). NMDA receptor-depen- dent ocular dominance plasticity in adult visual cortex. Neuron 38:977–985.

Schroeder, C. E., Tenke, C. E., Givre, S. J., Arezzo, J. C., and Vaughan, H. G., Jr. (1991). Striate cortical contribution to the surface-recorded pattern-reversal VEP in the alert monkey. Vision Res. 31:1143–1157.

Sherman, J. (1979). Visual evoked potential (VEP): Basic concepts and clinical applications. J. Am. Optom. Assoc. 50:19–30.

Sherman, S. M., and Wilson, J. R. (1975). Behavioral and morphological evidence for binocular competition in the postnatal development of the dog’s visual system. J. Comp. Neurol. 161: 183–195.

Shuler, M. G., and Bear, M. F. (2006). Reward timing in the primary visual cortex. Science 311:1606–1609.

Sokol, S. (1976). Visually evoked potentials: theory, techniques and clinical applications. Surv. Ophthalmol. 21:18–44.

Tagawa, Y., Kanold, P. O., Majdan, M., and Shatz, C. J. (2005). Multiple periods of functional ocular dominance plasticity in mouse visual cortex. Nat. Neurosci. 8:380–388.

Takahashi, T., Svoboda, K., and Malinow, R. (2003). Experience strengthening transmission by driving AMPA receptors into synapses. Science 299:1585–1588.

Teyler, T. J., Hamm, J. P., Clapp, W. C., Johnson, B. W., Corballis, M. C., and Kirk, I. J. (2005). Long-term potentiation of human visual evoked responses. Eur. J. Neurosci. 21:2045– 2050.

Van Hooser, S. D., Heimel, J. A., Chung, S., Nelson, S. B., and Toth, L. J. (2005). Orientation selectivity without orientation maps in visual cortex of a highly visual mammal. J. Neurosci. 25:19–28.

Van Sluyters, R. C., and Stewart, D. L. (1974). Binocular neurons of the rabbit’s visual cortex: Effects of monocular sensory deprivation. Exp. Brain Res. 19:196–204.

Whitlock, J. R., Heynen, A. J., Shuler, M. G., and Bear, M. F. (2006). Learning induces long-term potentiation in the hippocampus. Science 313:1093–1097.

Wiesel, T. N., and Hübel, D. H. (1963). Single-cell responses in striate cortex of kittens deprived of vision in one eye. J. Neurophysiol. 26:1003–1017.

Zhang, L. I., Tao, H. W., and Poo, M. (2000). Visual input induces long-term potentiation of developing retinotectal synapses. Nat. Neurosci. 3:708–715.