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

It is arguably the case that more is known about retinal ganglion cells (RGCs) in species commonly used in vision research, such as cat and monkey, than any other neurons in the CNS (Chalupa and Werner, 2004). In part, this reflects the paramount importance of vision in our lives, and the study of RGCs is vital to understanding how the visual system processes information. But it is also the case that RGCs have become important for understanding how neurons develop and form appropriate connections both over long (axonal pathfinding and target recognition in the brain) and short distances (formation of dendritic synapses and lamination in the inner plexiform layer, IPL). The advantages of the mouse model for addressing developmental issues are well recognized, yet our understanding of the morphological, functional, and developmental properties of mouse RGCs is still rudimentary. In recent years, however, a number of laboratories have begun making significant inroads with studies of mouse RGCs. In this chapter we summarize these recent advances and place them in an appropriate historical context.

Distinguishing retinal ganglion cell classes

A fundamental issue in the study of RGCs is defining the different cell classes constituting this population of neurons and categorizing each cell class in such a way that researchers in different laboratories can agree on their identity. The features distinguishing RGC classes are multiple and include morphological and functional properties, as well as their patterns of projections. In addition, the somata of a given cell class are presumed to be distributed across the retinal surface in nonrandom fashion with relatively little overlap of dendrites, to allow each RGC class to efficiently extract information from the entire visual field. Collectively, this has led to the important concept of parallel visual pathways or channels, which holds that different cell classes are specialized for processing and conveying different types of visual information to different retinorecipient targets.

In the mouse, we still lack basic information on the multiple criteria that have been used to distinguish among RGCs

in some other species. Nevertheless, progress has been made on this front, particularly in the use of morphological criteria for differentiating among mouse RGC classes. In the past, studies of mouse RGCs relied on categorizations of these cells in other mammals to identify different cell types in the mouse; for instance, RGCs with large somata and dendritic fields were termed alpha cells, in reference to cells described in other species (see Peichl et al., 1987). A perusal of the published photomicrographs suggests, however, that the mouse RGCs identified as alpha are not the same cell types in the different studies that have used this designation (compare Pang et al., 2003, Lin et al., 2004, and Völgyi et al., 2005). There may indeed be alpha-equivalent RGCs in the mouse (Peichl et al., 1987), but a simple description of a large soma and dendritic field is inadequate for reproducible identification of these neurons.

In comparison to some other species, clear morphological distinctions among the majority of mouse RGCs are difficult to discern by eye. For this reason, distinguishing among different mouse RGCs requires painstaking morphometrics. But there is an advantage to studying mouse RGCs, besides the power of genetic manipulation: mouse RGCs show no discernible differences in size with retinal eccentricity. This uniformity across the retina simplifies the study and identification of different cell classes.

Morphological descriptions of RGCs have traditionally relied on the injection of individual cells with Lucifer yellow or other dyes, which is time-consuming, or the retrograde transport of dyes or particles injected into retinorecipient regions, a method that does not always reveal the full extent of dendrites (see Doi et al., 1995). Recently, new methods have been developed that make imaging of many isolated, completely labeled RGCs more straightforward. One such technique is diolistics, a modified gene gun method in which tiny particles (1–2 μm in diameter) coated with lipophilic dyes such as DiI are propelled into the tissue to be labeled using a gene gun (Gan et al., 2000). A subset of cells is hit by the particles, and the dye becomes incorporated into the membranes and diffuses throughout the perimeter of the cell, allowing fine cell structures such as spines to be readily

visualized. Other workers have developed transgenic mice in which reporter genes, fluorescent proteins or alkaline phosphatase, are linked to genes expressed in RGCs (Feng et al., 2000; Badea et al., 2003). In particular, Feng et al. (2000) developed a number of mouse lines in which the expression of fluorescent proteins is linked to a regulator of the Thy-1 gene. Thy-1 is a protein found in RGCs whose function is unknown. Two of these mouse lines (M and H) have been used to visualize individual RGCs (Kong et al., 2005; Coombs et al., 2006). Other mice in which alkaline phosphatase expression is controlled by Cre-mediated recombination triggered by injections of 4-hydroxytamoxiphen have also been used successfully to visualize mouse RGCs (Badea et al., 2003; Badea and Nathans, 2004). These labeling methods, used alone (Sun et al., 2002) or in combination with new microscopy techniques and software that expedites morphological analysis, have prompted the erection of four proposed classification schemes for mouse RGCs (Badea and Nathans, 2004; Kong et al., 2005; Coombs et al., 2006). Each suggests a similar number of cell types, yet reconciling these four classifications remains problematic (e.g., figure 16 in Kong et al., 2005).

Sun et al. (2002) categorized mouse RGCs into different groups based mainly on qualitative criteria, as well as measurements of soma and dendritic field sizes. The resulting groupings showed a substantial degree of overlap, so in many cases, assigning a given cell to one group or another appears arbitrary. Badea and Nathans (2004) and Kong et al. (2005) used cluster analyses to sort out RGC types, but both studies relied primarily on only three cell traits in their analyses. Badea and Nathans (2004) used depth of dendritic stratification in the IPL (the location of both the topmost and the bottom-most dendrites) plus arbor area in their initial

analysis, then relied on other parameters to sort out clusters that looked similar to each other. Kong et al. (2005) also used three measurements in their cluster analysis: dendritic stratification depth, arbor area, and dendrite density (dendrite length/arbor area). This approach was not able to distinguish as a separate group the melanopsin-expressing RGCs, which have a clearly distinctive morphology.

In an attempt to circumvent these problems, we used 14 different morphological measures to perform hierarchical cluster analyses (figure 15.1; monoand bistratified cells were analyzed separately), using cells labeled with a melanopsin antibody as a control group to monitor the validity of the analysis (Coombs et al., 2006). Contrary to the assertion of others (e.g., Kong et al., 2005), we found that a larger number of parameters increased the power of the analysis rather than diminishing it. We also found that the analysis was more successful if we standardized each trait, by transforming the frequency distribution of each parameter to approximate a Gaussian curve and normalizing this curve to eliminate weighting due to differences in numerical scale. For example, without standardization, the dendritic field area (scale: 104 μm2) would have much more sway over the final clustering outcome than the dendritic field diameter (scale: μm). The analysis resulted in 14 different clusters, with clusters 4 and 5 likely representing two RGC classes each (figures 15.2 and 15.3). The cells in this study were labeled in one of four different ways: with melanopsin antibody, by dioloistics, with Lucifer yellow, and by transgenic expression of YFP (H line). All the melanopsin-positive cells were clustered into a single group (cluster 6; x’s in figure 15.1). The diolistically labeled cells were spread relatively evenly through the resulting clusters (though none appeared in cluster 6), but there were too few of the Lucifer yellow–

A 400

ON and OFF

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Figure 15.1 Cluster analysis trees. Linkage distance ( y-axis) shows the relative similarity of cells (along x-axis) for monostratified (A) and bistratified cells (B). Gray lines indicate abrupt increases in linkage distance, thus demarking a cutoff point for defining distinct clusters. Cells linked together below the gray lines are defined as

B 400

ON/OFF

300

200

100

0

single cell types and given group numbers (shown under the trees). One cell forms its own cluster (* in B) and is not given a group name. YFP-expressing cells (shaded boxes) and melanopsin-positive cells (×) are shown below the x-axes. All other cells were labeled with DiI or Lucifer yellow.

Figure 15.2 Tracings of cells from the monostratified cell clusters. Examples of ON and OFF cells are shown for groups M3, M6, M7, and M9. For groups M4 and M5, examples of two dif-

ferent morphologies (a and b) found in each cluster are shown. Scale bar = 100 μm.

filled cells to see any cluster trend for these. And though YFP-expressing cells were found in every cluster except cluster 11, they tended to be more heavily represented in 6 of the 14 clusters. This last observation suggests a bias for YFP to be expressed in specific RGC types in the H line of YFP-expressing mice (see figure 15.1, shaded boxes below x-axis).

Functional properties

The functional properties of mouse RGCs have been assessed by means of extracellular recordings from individual cells, multielectrode array recordings from multiple neurons, and whole-cell patch-clamp recordings. An early study by Stone and Pinto (1993) relied on extracellular recordings from individual neurons and reported that most mouse RGCs (90%) had concentric center-surround receptive fields (RFs), while the remaining 10% responded to both light onset and offset. Recently, three different response patterns were noted in alpha-like RGCs—an ON response to light onset and two types of OFF responses, transient or sustained, to light offset (Pang et al., 2003). A microelectrode array study reported four different response patterns to a simple step change in light: an increased firing rate to light onset, light offset, or to both onset and offset, and a decreased firing rate in response to light onset (Nirenberg and Meister, 1997). Moreover, these investigators noted that after the selective ablation of a population of amacrine cells situated in the ganglion cell layer (GCL), RGCs that normally responded to increases in light levels with transient responses showed sustained responses.

A recent multielectrode array recording study has suggested the presence of five different functional classes defined by a cluster analysis based on response latency, duration, relative size of ON and OFF responses, and the degree of nonlinearity of responses (Carcieri et al., 2003). It remains to be established how these functionally defined cell types relate to the 14 classes of mouse RGCs defined on the basis of morphological criteria.

A patch-clamp study of mouse RGCs defined these cells on the basis of their large sodium currents (Tian et al., 1998). Such cells showed synaptic events mediated by GABA and glutamate, with half of these also showing spontaneous synaptic events mediated by glycine. No cholinergic-medi- ated spontaneous synaptic events were noted. It remains to be established whether or not all classes of mouse RGCs express the same ionic conductances and show equivalent transmitter-mediated synaptic events.

Intrinsically photosensitive retinal ganglion cells

Mice without rods and cones in their retinas can still respond to light with normal pupillary reflexes and light-dependent

photoentrainment. These responses were found to be mediated by cells in the inner rather than the outer retina, namely, by a class of intrinsically photosensitive RGCs (ipRGCs) that express melanopsin (Provencio et al., 1998, 2002; Hattar et al., 2002; Ruby et al., 2002; Berson, 2003; Panda et al., 2003). There is also intriguing evidence that ipRGCs may be involved in some aspects of visual processing as well (Barnard et al., 2006). They have dendrites in the inner or outer laminae (or both) of the IPL, and synapse on amacrine and bipolar cells in the ON lamina and only amacrine cells in the OFF lamina (Belenky et al., 2003). This suggests that the responses of ipRGCs to light in the inner retina may be modulated by inputs from rods and cones in the outer retina (Belenky et al., 2003). A recent study has indeed shown a direct influence of rods on ipRGCs (Doyle et al., 2006).

Projections of mouse retinal ganglion cells

There are two sets of targets in the mouse brain to which RGCs project axons, depending on whether the pathway is image forming or non-image forming (Provencio et al., 1998). Image-forming RGCs send axons to the lateral geniculate nucleus (LGN, both dorsal and ventral) and the superior colliculus (SC), with more than 70%, and possibly all, RGCs projecting to the SC (Hofbauer and Drager, 1985). Transgenic mouse lines linking expression of the GAP-lacZ protein to that of Brn-3b have been used to show that RGCs located in the dorsal half of the retina send axons to the lateral region of the SC and to the dorsal lateral geniculate nucleus (dLGN) and ventral lateral geniculate nucleus (vLGN), while RGCs in the ventral retina send axons to the medial region of the SC as well as the LGN (Zubair et al., 2002). Other studies have used a similar method to look at the axonal projections of ipRGCs. Although the bulk of RGCs send information to the visual centers in the brain, ipRGCs project to central circadian centers: the suprachiasmatic nucleus (SCN), intergeniculate leaflet of the thalamus, and the ventral lateral geniculate, as well as the olivary pretectal nucleus, which mediates pupil reflexes (Provencio et al., 1998; Hattar et al., 2002, 2006). Interestingly, a recent report has shown that these cells also project to brain nuclei involved in vision information processing, such as the dLG (Hattar et al., 2006).

Molecular markers for retinal ganglion cells

Ultimately, the definitive factor for differentiating among different classes of RGCs, as for all neurons in the CNS, will be some combination of genes and molecules that are uniquely expressed in all members of a given cell class. Presumably, their expression would account for the set of morphological and functional attributes that distinguish these

cells from other cell classes. At present, we are a long way from attaining this long-term goal. Indeed, the ipRGCs that express melanopsin are the only cell class thus far identified on the basis of a molecular marker. Because these cells are molecularly identifiable based on their expression of this protein, a wealth of information has been obtained using genetic manipulations that tag reporter genes to the expression of melanopsin.

Specific markers for other RGCs have not been discovered, though there is information that junctional adhesion molecule-B ( JAM-B) is expressed in the GCL of mice almost exclusively in asymmetric OFF RGCs (Kim et al., 2006). Antibodies against neurofilament H have been reported to label alpha-type cells in the mouse (Lin et al., 2004); however, a common antibody against this protein (SMI-32) has been shown to label more than one type of RGC in YFPexpressing mice (Coombs et al., 2006). Thy-1, a thymus protein, is found in all RGCs (Barnstable and Drager, 1984) and is often used to differentiate RGCs from other retinal cell types, but is not specific to any single type of RGC. Another widespread protein found in RGCs is islet-2, which is expressed in about a third of mouse RGCs; these neurons appear to all project to the opposite (or contralateral) side of the brain (Pak et al., 2004). Conversely, the transcription factor Zic2 is found only in the ventral/temporal (VT) part of the retina, where ipsilaterally projecting RGCs are located (Herrera et al., 2003).

Other possible markers for specific RGC types in the mouse include connexins 36 and 45, which are expressed by alpha-type and bistratified RGCs, respectively (Schubert et al., 2005a, 2005b; Völgyi et al., 2005). Connexin 36 (Cx36) is responsible for the formation of gap junctions between OFF alpha-type RGCs and amacrine cells. ON alpha-type cells show no tracer coupling with each other but do so with two amacrine cell types in the GCL. Some of this coupling is lost in Cx36 knockout mice. OFF alpha-type cells are tracer coupled with each other, in addition to some amacrine cell types. The homologous coupling remains intact in the Cx36 knockout, but the coupling of the OFF RGCs with amacrine cells is lost (Völgyi et al., 2005). As more molecular markers specific to different RGC types are found, it will be of interest to determine to what degree these can be related to the different cell classes differentiated on the basis of morphological and functional criteria.

Generation and differentiation of retinal ganglion cells

All retinal neurons are generated from the same ventricular cells in the developing mouse retina. Among the first retinal cells to be born from these progenitor cells are RGCs, starting around embryonic day 11 (E11; Young, 1985). Two distinct patterns of ganglion cell generation have been

described, depending on the laterality of their projections. The vast majority of RGCs send axons to the opposite side of the brain (Drager and Olsen, 1980). These are born in a wave across the retinal surface, starting near the optic nerve head around E11, radiating outward, and ending at the retinal periphery, around E19–P0 (postnatal day zero; Drager, 1985). Conversely, RGCs with axons that project ipsilaterally (ca. 3% of RGCs in the GCL) originate in the VT crescent, though RGCs born in the VT crescent after E16.5 project contralaterally (Drager, 1985). A much larger percentage of the displaced RGCs (somata in the inner nuclear layer) send their axons ipsilaterally (ca. 30% vs. 3%).

RGC birth peaks around E13 (Drager, 1985), at a time when axons can be seen in the optic stalk (Hinds and Hinds, 1974). At P0, after all RGCs have been born, a large number of pyknotic cells become evident in the GCL, most of which are presumed RGCs. This cell death peaks around P3 and appears to radiate out from the optic nerve head region, ending around P11 in the peripheral retina (Young, 1984). Others have confirmed that most, if not all, RGC death occurs postnatally (Linden and Pinto, 1985; Pequignot et al., 2003; Farah and Easter, 2005). The incidence of cell death for RGCs generated earlier in development is somewhat higher than that for RGCs generated later in development. Farah and Easter (2005) reported that more than 48% of RGCs generated before E12.5 are eliminated by cell death, while about 30% of RGCs born after E15.5 succumb to this fate.

In mouse as in other animals, RGCs are the first cells to exit the mitotic cycle from a set of retinal progenitor cells (RGCs) that produce all neural cells in the retina. A host of molecular factors, both extrinsic and intrinsic, are emerging from studies dealing with the factors that control cell fate. Two secreted factors have been implicated in the early determination of mouse RGCs: sonic hedgehog (Shh; Wang et al., 2005) and growth and differentiation factor 11 (GDF11; Kim et al., 2005). Both molecules are expressed in central to peripheral waves across the retina starting around E12, just behind the leading edge of RGC birth, and have a negative effect on RGC production. The loss of either Shh or GDF11 increases the number of RGCs born, while an overproduction of either factor inhibits RGC birth (Kim et al., 2005; Wang et al., 2005). However, the mechanisms by which these two factors work are different. In the absence of Shh, RPCs tend to exit the cell cycle early, thus promoting an increase in RGC production (Wang et al., 2005). Moreover, RGCs appear to secrete Shh, thereby causing a cessation of further RGC production ( Jensen and Wallace, 1997; Wang et al., 2005; in chick: Zhang and Yang, 2001). Mice transgenic for a null allele of GDF11 show normal cell proliferation but are unable to make the switch from producing RGCs to making other retinal cells. The number of RGCs

is normal until about E17; after this time, when wild-type animals are showing a decrease in RGC production, these transgenic mice continue to generate RGCs (Kim et al., 2005).

A hierarchical suite of transcription factors appears to direct cell fate decisions during the course of RGC development. The homeobox gene Pax6 directs optic vesicle formation and at a later stage is required for the maintenance of multipotency in mitotic retinal progenitor cells (Marquardt et al., 2001). Only amacrine cells are found in retinas of mice with Pax6 conditionally knocked out (Marquadt et al., 2001). Starting at E10.5 and persisting through E15.5, a radial gradient of Pax6 expression is seen across the mouse retina, with the weakest expression near the future optic nerve head (Marquardt et al., 2001; Baumer et al., 2002). The expression of subsequent transcription factors signals the commitment of retinal progenitor cells to specific retinal cell lineage fate. In the case of RGCs, the basic helix-loop-helix transcription factor Math5 (Atoh7) is expressed in postmitotic cells (Yang et al., 2003), just before the first RGCs are born (Brown et al., 1998). Math5 is expressed in a temporal wave, beginning near the future optic nerve at E11 and moving toward the retinal periphery in a pattern reminiscent of RGC births (Brown et al., 1998; Wang et al., 2001). In mice lacking Math5, the production of most RGCs is inhibited; however, about 20% of RGCs may still be found in adults, suggesting the presence of a Math5-independent RGC pathway (Brown et al., 2001; Wang et al., 2001). Moreover, Math5 is not sufficient to ensure a RGC fate, since it has also been found in other retinal cell types (Yang et al., 2003). Thus, other factors are required to commit these cells to an RGC fate (Mu et al., 2005).

Downstream of Math5 and first seen at E12, a POU domain transcription factor, POU4f2 (formerly Brn3b), is activated that promotes the expression of RGC phenotypic features such as axon elongation and pathfinding (Xiang et al., 1993; Erkman et al., 1996, 2000; Gan et al., 1996; Xiang, 1998; Brown et al., 2001; Wang et al., 2001; Yang et al., 2003). Even so, this transcription factor is not responsible for specification of RGC fate (Gan et al., 1999); thus there remains a missing link between Math5 and RGC determination. POU4f2 is first seen in postmitotic RGC precursors as they migrate from the neuroblast layer to the inner retina (Gan et al., 1996). The absence of POU4f2 expression causes an increase in the death of RGC precursors, leading to a loss of about 70% of RGCs from the mature retina (Xiang, 1998; Gan el al., 1999). In mice lacking the Wilms’ tumor gene Wt1, no POU4f 2 expression is seen, and the phenotype of the mice is similar to those lacking POU4f 2 (Wagner et al., 2002). Two other POU domain transcription factors are found in RGCs in the mouse, POU4f1 and POU4f3 (formerly Brn3a and Brn3c).

The three POU domain transcription factors have slightly different spatiotemporal expression patterns (Xiang et al., 1995, 1996; Erkman et al., 1996). All three play a role in RGC development, notably axon growth (Erkman et al., 1996; Xiang, 1998; Wang et al., 2002; Pan et al., 2005; Quina et al., 2005) and have the ability to substitute for one another when expressed in the appropriate time and place (Wang et al., 2002; Pan et al., 2005). At the same time, each may play a unique role in the development and differentiation of certain RGC properties; for instance, POU4f3 may control ipsilateral axon growth (Wang et al., 2002). Mice lacking two murine homologues of the Drosophila gene distalless (Dlx1 and Dlx2) also show a reduction in RGC number, acting upstream of the POU domain factors (de Melo et al., 2003, 2005).

Development of retinal ganglion cell morphological properties

Shortly after RGCs are born, they begin to extend axons into the optic nerve (Hinds and Hinds, 1974), and these reach the optic chiasm by E12–E13 (Godement et al., 1984, 1987; Zubair et al., 2002) and the dLGN and SC by E15–E16 (Godement et al., 1984; Edwards et al., 1986; Zubair et al., 2002). Within the retina, dendrites can be seen in the nascent IPL around the time of birth (E19 or P0). RGC dendrites grow and mature during the two postnatal weeks and appear morphologically mature by P20 (figure 15.4). As the dendritic trees extend and elaborate outward in the plane of the growing IPL, the orthogonal (or vertical) extent of these dendrites in the IPL remains relatively constant, even as the IPL itself widens. Thus, RGC dendrites stratify early in the postnatal development of the mouse retina (Coombs et al., 2007), though rearrangements of stratification pattern may occur at later stages (see Tian and Copenhagen, 2003).

The same morphological measurements used to distinguish among different RGC classes in the adult mouse have also been applied to RGCs on different postnatal days (Coombs et al., 2007). This effort revealed three different developmental trends. Five of the parameters showed little or no change. Five others increased steadily until around eye opening, after which these measures declined to reach adult-like values. And three other parameters showed little or no change early in postnatal development, then quickly increased to adult-like levels, showing an overall sigmoid shape in their growth pattern (figure 15.5). Thus, RGC dendritic growth appears to be regulated by different factors, all acting during the early postnatal period.

Development of retinal ganglion cell functional properties

The first synapses of RGCs are conventional, formed with amacrine cells, starting on P3 and ending around P20.

Figure 15.4 Tracings of immature RGCs, bird’s-eye and side views (top and bottom, respectively, in each row). Five different ages are shown in rows from top to bottom: P1, P4, P8, P12, and P20.

Ribbon synapses with bipolar cells are seen later in development, starting on P11, around the time of eye opening, and reaching a maximum density around P20 (Fisher, 1979). Correlated with this temporal sequence of synapse formation, waves of electrical and calcium activity move across the retina in large patches. The waves of activity seen between P1 and P10 are driven by cholinergic transmission, while subsequent waves are dependent on glutamate, correlating with the formation of synapses between RGCs and bipolar cells (Bansal et al., 2000). These waves of activity have been implicated in the refinement of RGC projection patterns (for reviews, see Torborg and Feller, 2005; see also chapter 28, this volume).

Lines in the side views represent the boundaries of the IPL, with the GCL on top and the INL on the bottom. Scale bar = 50 μm.

Spontaneous synaptic events are relatively infrequent before eye opening, with the number of such events recorded from RGCs increasing dramatically about 2 weeks after eye opening (Tian and Copenhagen, 2001). Using multielectrode array recordings, more than half of RGCs just before eye opening have been shown to respond to both On and Off changes in light. The incidence of ON/OFFresponsive cells decreases to the adult level of about 20% by 30 days after birth. This physiological change has been correlated with changes in the dendritic morphology occurring over the same time period. The percentage of the RGC population with both the physiological and anatomical properties of ON/OFF-responsive cells remains fixed if the

Figure 15.5 Thirteen different morphological measurements of developing mouse RGCs showed three main growth patterns. A, Little or no change was seen for five of the measurements. Top to bottom, number of dendrites, branch angle, symmetry (location of the soma in the dendritic field in bird’s-eye view), tortuosity (the curviness of dendritic branches), and axon diameter. B, Five measurements showed a growth pattern characterized by linear growth, peaking around P11–P12, followed by decreases described by single exponential decays. Top to bottom, total dendrite length, spine density,

mice are dark-reared (Tian and Copenhagen, 2003). A recent study from our laboratory, however, has shown that the percentage of bistratified cells (i.e., those with dendrites stratified in two distinct strata of the IPL) is relatively constant throughout postnatal development and equivalent to the incidence found at maturity (Coombs et al., 2007). Since the dendrites of many developing RGCs are stratified near the center of the IPL, it is possible that these could be innervated transiently by both ON and OFF bipolar cells,

number of branches, dendrite diameter, and the highest branch order for one dendrite. C, Three parameters followed a sigmoid growth pattern: little or no early change, fast change, followed by little or no change. Top to bottom, soma area, dendritic field area, and mean branch length. The changes in the means with age were fit by sigmoid curves (black lines). All fits were determined by the mean values at each age (black lines on each graph). The number of individual cells is the same in each graph, although some graphs appear to have fewer cells, owing to overlapping measurements.

which would account for the apparent discrepancy between our morphological findings and the physiological results of Tian and Copenhagen (2003). However, these authors also reported a higher than normal percentage of RGCs with bistratified dendrites just before eye opening.

About 4 days after eye opening, the retinal waves that traverse the retina during development start to deteriorate, and by P21 they are gone. Unlike changes in the percentage of ON/OFF cells recorded in mouse retina, the loss of retinal

waves is not dependent on visual experience, as they are lost over the normal time period when mice are dark-reared (Demas et al., 2003).

Early in development, before rods and cones are functional, ipRGCs can respond to light (Sekaran et al., 2005; Tu et al., 2005; Lupi et al., 2006). And though ipRGCs make up about 1% of the adult RGCs in the mouse, they account for more than 13% of ganglion cells on P0. Also, there are functional connections to the SCN at P0 in normal mice, but innervation of the SCN is not seen until P14 in mice lacking melanopsin (Sekaran et al., 2005). Multielectrode array recordings from early postnatal mouse retinas show three different physiological responses to light (in the absence of retinal waves), indicating three types of ipRGCs in these young retinas. Only two of these response types were also seen in the adult (Tu et al., 2005).

Concluding remarks

Mice are proving to be a remarkable resource for studies of RGCs in particular and the visual system in general. Though the visual capabilities of the mouse are relatively poor, increasingly sophisticated techniques for manipulating the mouse genome are already providing advances in our understanding of the visual system. Undoubtedly, we can look forward to more advances as more and more investigators become convinced of the utility of the mouse for their studies of the visual system.

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