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

surrounded by a single area, V2, containing multiple compartments with distinct connections and RF properties embedded in a single global visuotopic map (Roe and Ts’o, 1995), V1 in mice is adjoined by multiple areas, each of which contains a map of the entire visual field. This organization exhibits the hallmark feature of a complex extrastriate cortex and supports the hypothesis that in ancestral mammals, V1 was surrounded by multiple areas that gave rise to homologous areas in distantly related species (Rosa and Krubitzer, 1999).

Relationship between Cytoarchitectonic Areas and

Topographic Maps To determine the shape and size of extrastriate visual areas, Wang and Burkhalter (2007) traced the connections from the perimeter of V1. The borders of the nine visuotopically organized areas are shown in the flat map illustrated in figure 20.1D. The overlay of the topographic map with the cytoarchitectonic map of Caviness and Frost (1980) shows that in medial extrastriate cortex, PM and AM overlap with area 18b, whereas in lateral extrastriate cortex, P, LM, AL, LI, RL, and A overlap with areas 18a and 36a, which may correspond to POR (see figure 20.1A). The overlay of Wang and Burkhalter’s (2007) map with the cytoarchitectonic map of Paxinos and Franklin (2001) shows that V2ML in medial extrastriate cortex overlaps with PM and AM (see figure 20.1B). In lateral extrastriate cortex, V2L coincides with P, LM, LI, AL, RL, A, and POR, which encroaches on ectorhinal cortex (see figure 20.1B).

Connections of mouse visual cortex

Subcortical Inputs In the mouse, at least 12 different morphological types of retinal ganglion cells (RGCs) have been identified that convey image-forming and non-image- forming visual information from the eye to a variety of subcortical structures, including the dorsal lateral geniculate nucleus (dLGN) and the superior colliculus (SC) (Godement et al., 1984; Sun et al., 2002; Badea and Nathans, 2004; Hattar et al., 2006). Based on morphological criteria, 11–14 different types of RGC have been identified in the mouse retina (Kong et al., 2005; Coombs et al., 2006). The imageforming RGCs have been classified into three to five distinct groups with shortand long-latency responses (Carcieri et al., 2003; Pang et al., 2003). Short-latency neurons are further classified as ONand OFF-center cells, and ON neurons are subdivided into separate groups with transient and sustained response properties (Carcieri et al., 2003). But, unlike recordings in the isolated retina (Stone and Pinto, 1993), in vivo studies have found that linear and nonlinear spatial summation properties of RGC RFs lie on a continuum with various degrees of nonlinearities, and there is no evidence for distinct classes of cells with linear (X-like) and

nonlinear (Y-like) RFs (Carcieri et al., 2003). This differs from mouse and squirrel dLGN, in which most RFs show linear spatial summation properties and resemble monkey magnocellular dLGN neurons (Usrey and Reid, 2000; Grubb and Thompson, 2003; Van Hooser et al., 2003). Although there is no evidence for distinct linear and nonlinear channels, ON-center dLGN cells are more sensitive to contrast than OFF-center cells, suggesting that geniculocortical inputs are carried through parallel high- contrast-gain ON and low-contrast-gain OFF channels (Grubb and Thompson, 2003).

Neurons of the dLGN send axons to the visual cortex, where they terminate in layers 1, 3, 4, and the layer 5/6 border of V1 (Frost and Caviness, 1980; Simmons et al., 1982). Individual axonal arbors have different laminar distributions, terminal densities, and fields of innervation, which in layer 4 are 50–1,700 μm in diameter (Antonini et al., 1999). Descending outputs from V1 to the dLGN originate from layer 6 (Simmons et al., 1982; Brumberg et al., 2003), whereas layer 5 cells send output to the SC (Kozloski et al., 2001).

About 90% of retinal inputs project to the opposite hemisphere (Dräger and Olson, 1980). Cortical inputs from the contralateral dLGN are distributed across the entire primary visual area, whereas inputs from the same side terminate in the lateral half of V1, which corresponds to the binocular zone (Dräger, 1974; Antonini et al., 1999; Kalatsky and Stryker, 2003).

Connections within V1 Most connections within V1 are local but account for only 3.5% of the total length of 4 km of axons contained within 1 mm3 of cortex (Braitenberg and Schüz, 1991; Schüz et al., 2006). Studies in the adult mouse somatosensory cortex suggest that approximately 85% of these axons are excitatory and 15% are inhibitory (DeFelipe et al., 1997). Although in mouse visual cortex, isolated examples of spiny stellate cells have been described that project from layer 4 to layer 2/3 (Valverde, 1968, 1976), interlaminar connections of pyramidal neurons have only been studied systematically in somatosensory cortex. In mouse S1, Larsen and Callaway (2006) found that layer 2/3 pyramidal cells either project to both layers 5 and 6 or make connections to layers 4, 5, and 6. Further, Larsen and Callaway (2006) identified three types of layer 5 pyramidal cells with distinct dendritic arbors that all send axonal projections to layers 2/3 and 6. An even greater diversity of pyramidal cell types was observed in layer 5 of V1, but whether these cells have different connections is not known (Tsiola et al., 2003). Corticogeniculate layer 6 neurons, however, are known to send recurrent axon collaterals to layer 4 (Brumberg et al., 2003). Taken together, this sketchy evidence suggests that V1 contains a columnar network that links chains of neurons, which act as conduits for the

propagation of ascending and descending sequences of spontaneous neuronal firing that have been observed with calcium indicator dyes in slices of mouse visual cortex (Ikegaya et al., 2004).

The horizontal connections within layers 2/3, 5, and 6 of V1 are anisotropic and are longer in rostrocaudal axis than in mediolateral axis (Q. Wang and A. Burkhalter, unpublished observations). This phenomenon is location dependent and more prominent in the upper than the lower visual field representation. Within this oval region, the distribution of terminals is uniform and resembles the nonpatchy horizontal connections within V1 of the gray squirrel (Van Hooser et al., 2006). This differs from earlier claims of patchy horizontal connections within rat V1 (Rumberger et al., 2001). However, it is quite possible that individual cells or very small clusters make patchy intrinsic connections, as has been shown in rat visual cortex (Burkhalter and Charles, 1990).

Connections between Different Cortical Areas Little is known about interareal connections of mouse visual cortex. Early studies using 3H-proline as tracer found that V1 projects to as many as nine discrete projection fields (Olavarria et al., 1982; Olavarria and Montero, 1989). Using high-resolution pathway tracing with dextran dyes to label axon terminal fields in combination with bisbenzimide retrograde labeling of fixed callosal landmarks, we have found that mouse V1 projects to 15 fields (Wang and Burkhalter, 2007). These targets are best visualized in flat mounts of the injected cortical hemisphere. In the example shown in figure 20.2A, we injected three different dyes— fluororuby (red), fluoroemerald (green), and biotinylated dextran amine (BDA, yellow)—at different azimuths of the upper visual field representation in V1 (Wang and Burkhalter, 2007). Groups of nonoverlapping red/green and yellow projection patches were found in nine topographically organized extrastriate areas (i.e., LM, AL, RL, A, PM, AM, LI, P, and POR). In addition, we found projection fields in which the red, green, and yellow patches largely overlapped (see figure 20.2B–D). These nonvisuotopically organized fields include area 36p, the lateral entorhinal area (LEA), the face representation of area S1, the mediomedial area (MM), which overlaps with V2MM of Paxinos and Franklin (2001), the primary cingulate cortex (Cg1), and the retrosplenial agranular area (RSA). These results show that the connections of mouse V1 are more extensive than previously demonstrated (Olavarria and Montero, 1989), and that similar to what is seen in rat, V1 provides direct inputs to somatosensory cortex, the frontal eye field, and retrosplenial, perirhinal, and entorhinal cortex (Miller and Vogt, 1984; Coogan and Burkhalter, 1993).

There is only a single study on the connections of mouse extrastriate visual cortex, demonstrating that areas V1, 18a,

and 18b are reciprocally connected (Simmons et al., 1982). Our area map (see figure 20.1D) (Wang and Burkhalter, 2007) and the overlay with the map of Caviness and Frost (1980) (see figure 20.1A), however, suggest that the cytoarchitectonic areas 18a and 18b contain more than a single visuotopic map (see figure 20.1A). We have therefore sought to determine whether areas LM and AL, both of which are contained within area 18a, have distinct connections. Tracing the connections of area LM with BDA shows that this V2-like area has strong projections to areas V1, AL, RL, LI, P, POR, 36p, AM, and PM, and weaker projections to the rostral temporal area (TeAr), LEA, the dorsal auditory belt (AuD), retrosplenial cortex (RSA), and the frontal eye field (Cg1, not shown) (figure 20.3). These connections closely resemble those of rat LM (Coogan and Burkhalter, 1993) and show similarities to the projections labeled by tracer injections into the rat posterior lateral extrastriate cortex, which is strongly connected with the parahippocampal cortex and the amygdala (McDonald and Mascagni, 1996; Burwell and Amaral, 1998).

Tracer injections into area AL revealed a set of connections that differ from those of LM. The AL connections shown in figure 20.4 include strong projections to V1, LM, RL, LI, AM, PM, AuD, S1, the lateral parietal cortex (PL), area A of the posterior parietal cortex, the transition zone between cingulate and retrosplenial cortex (Cg/RS), Cg1, and the dorsal orbitofrontal area (DLO), and weak inputs to area P, POR, TeAr, 36p, and LEA. In the rat, similar connections were observed after injections into AL and rostral lateral extrastriate cortex, which, unlike posterior lateral cortex, is only very weakly connected with the amygdala (Coogan and Burkhalter, 1993; McDonald and Mascagni, 1996).

From these results it is evident that LM and AL share many targets. However, the projection strengths in these shared targets are not the same. For example, LM projects more strongly to area P, area LI, and 36p, whereas AL provides stronger inputs to AuD and A. An even stronger preference of LM for ventral targets is evident in the input to POR, which has very sparse connections with AL. In contrast, the strong preference of AL for dorsal targets is seen in the projections to PL, area Cg/RS, and DLO, which do not receive input from LM. These differences suggest that the projections of LM and AL contribute to distinct but intertwined visual processing streams (Wang and Burkhalter, 2003, 2004, 2005). In mice, the ventral stream appears to originate from LM and flows into parahippocampal (i.e., area POR) and perirhinal cortex (i.e., area 36p). Single-unit recordings have shown that LM neurons carry high spatial frequency information (Gao et al., 2006), which may be used by POR neurons to detect changes in the visual environment (Burwell and Hafeman, 2003). Lesion studies further suggest that the detected signals are used further downstream in

Figure 20.3 Intracortical connections of the extrastriate lateromedial area (LM) in mouse visual cortex, shown in tangential sections through the flattened posterior cerebral cortex. A, Fluorescence image showing the distribution of retrogradely labeled callosal connections. Dashed lines represent the myeloarchitectonic borders of V1, S1, and RSA. B, Darkfield image of biotinylated dextran amine

(BDA)–labeled axonal connections of area LM. Asterisk indicates the injection site. Note the strong connections to areas POR and 36p. C, Superimposition of BDA-labeled LM connections (gold) with callosal connections (blue somata). A, anterior; L, lateral; M, medial; P, posterior. Scale bar = 1 mm in all images. See color plate 9.

Figure 20.4 Intracortical connections of the extrastriate lateromedial area (AL) in mouse visual cortex, shown in tangential sections through the flattened posterior cerebral cortex. A, Fluorescence image showing the distribution of retrogradely labeled callosal connections. Dashed lines represent the myeloarchitectonic borders of V1, S1, and RSA. B, Darkfield image of biotinylated dextran amine

(BDA)–labeled axonal connections of area AL. Asterisk indicates injection site. Note the strong connections to areas PL, A, and Cg/RS. C, Superimposition of BDA-labeled LM connections (gold) with callosal connections (blue somata). A, anterior; L, lateral; M, medial; P, posterior. Scale bar = 1 mm in all images. See color plate 10.

perirhinal cortex to make visual discriminations and for object recognition (Prusky et al., 2004; Davies et al., 2007). Thus, the ventral stream may play a role in navigation that relies on the dynamic recognition and identification of landmarks along routes. In contrast, AL sends low-frequency information about rapidly changing, fast-moving objects (Gao et al., 2006) to polymodal areas in posterior and lateral parietal cortex, which in rat represent tactile and auditory stimuli (Toldi et al., 1986; Brett-Green et al., 2003). This information may be used further downstream in retrosplenial cortex and the frontal eye field to direct eye, head, and body movements (Neafsey, 1990; Taube, 1998). Thus, areas of the dorsal stream may process visual motion-related cues that may be employed for navigation and the construction of reference frames used for the generation of head direction cells and hippocampal place cells (Save et al., 2005).

Areal Hierarchy Most interareal connections in mouse visual cortex originate from layers 2/3 and 5 pyramidal neurons (Simmons et al., 1982). Feedforward projections from V1 to higher visual areas such as LM, AM, and S1 (viewed from the perspective of the visual system) were shown to terminate principally in layers 2/3–6 (Olavarria and Montero, 1989; Yamashita et al., 2003; Dong et al., 2004a; figure 20.5A). In contrast, feedback projections from the higher visual area, LM, terminate in layers 1, 2/3, 5, and 6 of V1 and exclude layer 4 (Yamashita et al., 2003; Dong et al., 2004a, 2004b) (figure 20.5B). These laminar connection patterns are reminiscent of those found in rat visual cortex, in which feedforward and feedback circuits interconnect areas to a hierarchical network (Coogan and Burkhalter, 1993). Although the reconstruction of the

Figure 20.5 Laminar organization of inter-areal feedforward and feedback connections in mouse visual cortex labeled by anterograde tracing with BDA. A, Coronal section showing feedforward axons that originate from the lower area V1 and terminate in the higher extrastriate area LM. The projection column includes layers 2/3 to 6, and inputs to layer 1 are sparse. B, Coronal section showing feedback axons that originate from area LM and terminate in V1. The projections to layer 1, 2/3, and 5 are dense, whereas inputs to layer 4 are sparse. Scale bar = 0.2 mm. See color plate 11.

structure of the areal hierarchy of mouse visual cortex is incomplete, multiunit recordings in different visual areas have shown significant areal differences in RF size (i.e., V1 < LM < POR < AL < P < LI < PM < AM < RL < A < MM; Wang and Burkhalter, 2007), suggesting that the structural hierarchy correlates with a functional hierarchy. The present anatomical evidence suggests that the neocortical hierarchy has at least four levels, including V1, LM/AL, POR/36p, and LEA.

Conclusion

The presence of 10 complete orderly maps of the visual field strongly suggests that mouse visual cortex contains at least 10 distinct visual areas. Thus, the arealization of mouse visual cortex rivals the complexity of that in prosimian monkeys (Striedter, 2006). Unlike in many other rodent and nonrodent mammals, however, lateral primary visual cortex in mice is adjoined by multiple distinct areas, not by a single area V2 containing repeating structurally and functionally distinct modules (Rosa and Krubitzer, 1999). Only one of these areas, LM, shares the vertical meridian representation with V1 and can therefore be considered homologous to V2. Thus, according to the complex cortex hypothesis, the remaining visuotopically organized areas can be considered homologous to extrastriate areas in other mammalian lineages (Rosa and Krubitzer, 1999). Unlike primate V2, however, LM, including all the other visual areas, contains maps that are topologically equivalent to V1. The reason for this mapping format may be that the mouse brain is small and there is little pressure to minimize the length of connections between homotopic locations of different maps (Allman and Kaas, 1974). Similar rules may apply to intra-areal connections and may explain the absence of patchy horizontal connections within mouse V1 (Chklovskii and Koulakov, 2004).

Geniculocortical inputs are conveyed in a high-contrast- gain ON channel and a low-contrast-gain OFF channel, both of which have linear spatial summation properties and resemble the magnocellular geniculocortical pathway in primates. In cortex, the distinction between highand lowcontrast pathways is lost. However, high spatial frequency/ low temporal frequency information is preferentially represented in area LM, whereas AL neurons are selective for fast-moving, low spatial frequency/high temporal frequency stimuli. Interestingly, the outputs of LM are strongly biased toward ventral cortex, whereas AL projects more strongly to dorsal areas. These connections are reminiscent of the “where” and “what” streams in primates (Ungerleider and Pasternak, 2004) and suggest that similar streams exist in mouse visual cortex.

Lower and higher visual areas are interconnected by feedforward and feedback circuits, which are identified by their

distinct laminar termination patterns. On the basis of these anatomical features, the few areas that have been studied so far can be ordered in a hierarchy that has at least 4 levels, with V1 at the bottom and entorhinal cortex at the top. By comparison, in macaque monkey there are 11 levels between V1 and entorhinal cortex (Felleman and Van Essen, 1991). But the lower number of levels found in mouse neocortex may not be surprising, given that the difference between the smallest and largest RFs in monkey is approximately 50 times greater than in mouse (Gao et al., 2006; Wang and Burkhalter, 2007). Thus, the shorter chain of command in mouse visual cortex suggests that the visual world is represented over a much narrower spatial scale than in primates. Although the mouse visual cortex is clearly very different from that in primates, both species share a basic common plan of organization, suggesting that mouse visual cortex is a good model for studies of arealization, hierarchical networks, interareal synaptic processing, and how visual inputs are used to construct an environment-independent spatial coordinate system.

acknowledgments Work was supported by grant nos. EY05935 and EY-016184 from the U.S. National Institutes of Health, grant no. HFSP123/200-B, and funding from the McDonnell Center for Studies of Higher Brain Function. We thank David C. Van Essen for the flat map of cytoarchitectonic areas shown in figure 20.1B.

REFERENCES

Allman, J. M., and Kaas, J. H. (1974). The organization of the second visual area (VII) in the owl monkey: A second order transformation of the visual hemifield. Brain Res. 76:247–265.

Antonini, A., Fagolini, M., and Stryker, M. P. (1999). Anatomical correlates of functional plasticity in mouse visual cortex. J. Neurosci. 19:4388–4406.

Badea, T. C., and Nathans, J. (2004). Quantitative analysis of neuronal morphologies in the mouse retina visualized by using a genetically directed reporter. J. Comp. Neurol. 480:331–351.

Braitenberg, V., and SchÜz, A. (1991). Anatomy of the cortex: Statistics and geometry. Berlin: Springer-Verlag.

Brett-Green, B., FifkovÁ, E., Larue, D. T., Winer, J. A., and Barth, D. S. (2003). A multisensory zone in rat parietotemporal cortex: Intraand extracellular physiology and thalamocortical connections. J. Comp. Neurol. 460:223–237.

Brumberg, J. C., Hamzei-Sichani, F., and Yuste, R. (2003). Morphological and physiological characterization of layer VI corticofugal neurons of mouse primary visual cortex. J. Neurophysiol. 89:2854–2867.

Burkhalter, A., and Charles, V. (1990). Organization of local axon collaterals of efferent projection neurons in rat visual cortex. J. Comp. Neurol. 302:920–934.

Burwell, R. D., and Amaral, D. G. (1998). Cortical afferents of the perirhinal, postrhinal, and entorhinal cortices of the rat. J. Comp. Neurol. 398:179–205.

Burwell, R. D., and Hafeman, D. M. (2003). Positional firing properties of postrhinal cortex neurons. Neuroscience 119:577–588.

Carcieri, S. M, Jacobs, A. L., and Nirenberg, S. (2003). Classification of retinal ganglion cells: A statistical approach. J. Neurophysiol. 90:1704–1713.

Caviness, V. S. (1975). Architectonic map of neocortex of the normal mouse. J. Comp. Neurol. 164:247–263.

Caviness, V. S., and Frost, D. O. (1980). Tangential organization of thalamic projections to the neocortex in the mouse. J. Comp. Neurol. 194:335–367.

Chklovskii, D. B., and Koulakov, A. A. (2004). Maps in the brain: What can we learn from them? Annu. Rev. Neurosci. 27: 369–392.

Coogan, T. A., and Burkhalter, A. (1993). Hierarchical organization of areas in rat visual cortex. J. Neurosci. 13:3749–3772.

Coombs, J., Van Der List, D., Wang, G.-Y., and Chalupa, J. M. (2006). Morphological properties of mouse retinal ganglion cells.

Neuroscience 140:123–136.

Dakin, S., and Frith, U. (2005). Vagaries of visual perception in autism. Neuron 48:497–507.

Davies, M., Machin, P. E., Sanderson, D. J., Pearce, J. M., and Aggleton, J. P. (2007). Neurotoxic lesions of the rat perirhinal and postrhinal cortices and their impact on biconditional visual discrimination tasks. Behav. Brain Res. 176:274–283.

DeFelipe, J., Marco, P., Fairen, A., and Jones, E. G. (1997). Inhibitory synaptogenesis in mouse somatosensory cortex. Cereb. Cortex 7:619–634.

De Vries, I. (1912). Über die Zytoarchitektonik der Grosshirnrinde der Maus und über die Beziehungen der einzelnen Zellschichten zum Corpus Callosum auf Grund von experimentellen Läsionen. Folia Neurobiol. (Haarlem) 6:289–322.

Dong, H., Shao, Z., Nerbonne, J. M., and Burkhalter, A. (2004a). Differential depression of inhibitory synaptic responses in feedforward and feedback circuits between different areas of mouse visual cortex. J. Comp. Neurol. 475:361–373.

Dong, H., Wang, Q., Valkova, K., Gonchar, Y., and Burkhalter, A. (2004b). Experience-dependent development of feedforward and feedback circuits between lower and higher areas of mouse visual cortex. Vision Res. 44:3389–3400.

DrÄger, U. C. (1974). Autoradiography of tritiated proline and fucose transported transneuronally from the eye to the visual cortex in pigmented and albino mice. Brain Res. 82:284– 292.

DrÄger, U. C. (1975). Receptive fields of single cells and topography in mouse visual cortex. J. Comp Neurol. 160:269–290.

DrÄger, U. C., and Olson, J. F. (1980). Origins of crossed and uncrossed retinal projections in pigmented and albino mice. J. Comp. Neurol. 191:383–412.

Eckert, M. A., Galaburda, A. M., Mills, D. L., Belluggi, U., Korenberg, J. R., and Reiss, A. L. (2006). The neurobiology of Williams syndrome: Cascading influences of visual system impairment? Cell. Mol. Life Sci. 63:1867–1875.

Felleman, D. J., and Van Essen, D. C. (1991). Distributed hierarchical processing in the primate cerebral cortex. Cereb. Cortex 1:1–47.

Fortuyn, A. (1914). Cortical cell-lamination of the hemispheres of some rodents. Arch. Neurol. Psychiatry 17:215–247.

Frost, D. O., and Caviness, V. S. (1980). Radial organization of thalamic projections of the neocortex in the mouse. J. Comp. Neurol. 194:369–393.

Gao, E., DeAngelis, G. C., and Burkhalter, A. (2006). Specialized areas for shape and motion analysis in mouse visual cortex.

Soc. Neurosci. Abstr. 641.6.

Garey, L. J. (2006). Brodmann’s localization in the cerebral cortex. New York: Springer-Verlag.

Godement, P., SalaÜn, J., and Imbert, M. (1984). Prenatal and postnatal development of retinogeniculate and retinocollicular projections in the mouse. J. Comp. Neurol. 230:552–575.

Grice, D. E., and Buxbaum, J. D. (2006). The genetics of autism spectrum disorders. Neuromolecular Med. 8:451–460.

Grubb, M. S., and Thompson, I. D. (2003). Quantitative characterization of visual response properties in the mouse dorsal lateral geniculate nucleus. J. Neurophysiol. 90:3594– 3607.

Hall, W. C., Kaas, J. H., and Diamond, I. T. (1971). Cortical visual areas in the grey squirrel (Sciurus carolensis): A correlation between cortical evoked potential maps and architectonic subdivisions. J. Neurophysiol. 34:43–452.

Hattar, S., Kumar, M., Park, A., Tong, P., Tung, J., Yau, K. W., and Berson, D. M. (2006). Central projections of melanopsinexpressing retinal ganglion cells in the mouse. J. Comp. Neurol. 497:326–349.

Hubel, D. H., and Wiesel, T. N. (1965). Receptive fields and functional architecture in two nonstriate visual areas (18 and 19) of the cat. J. Neurophysiol. 28:229–289.

Ikegaya, Y., Aaron, G., Cossart, R., Aronov, D., Lampl, I., Ferster, D., and Yuste, R. (2004). Synfire chains and cortical songs: Temporal modules of cortical activity. Science 304: 559–564.

Isenschmid, R. (1911). Zur Kenntnis der Grosshirnrinde der Maus.

Abhandl. Königl. Preuss. Akad. Wiss. 3:1–46.

Just, M. A., Cherkassky, V. L., Keller, T. A., Kana, R. K., and Minshew, N. J. (2007). Functional and anatomical cortical underconnectivity in autism: Evidence from fMRI study of an executive function and task and corpus callosum optometry.

Cereb. Cortex 17:951–961.

Kaas, J., Hall, W. C., and Diamond, I. T. (1970). Cortical visual areas I and II in the hedgehog: Relation between evoked potential maps and architectonic subdivisions. J. Neurophysiol. 33: 595–615.

Kalatsky, V. A., and Stryker, M. P. (2003). New paradigm for optical imaging: Temporally encoded maps of intrinsic signal. Neuron 38:529–545.

Kalia, M., and Whitteridge, D. (1973). The visual areas in the splenial sulcus of the cat. J. Physiol. 232:275–283.

Kong, J.-H., Fish, D. R., Rockhill, R. J., and Masland, R. H. (2005). Diversity of ganglion cells in the mouse retina: Unsupervised morphological classification and its limits. J. Comp. Neurol. 489:293–310.

Kozloski, J., Hamzei-Sichani, F., and Yuste, R. (2001). Stereotyped position of local synaptic targets in neocortex. Science 292:868–872.

Krieg, W. J. S. (1946). Connections of the cerebral cortex. J. Comp. Neurol. 84:278–323.

Larsen, D. D., and Callaway, E. M. (2006). Development of layer-specific axonal arborizations in mouse primary somatosensory cortex. J. Comp. Neurol. 494:398–414.

McDonald, A. J., and Mascagni, F. (1996). Cortico-cortical and cortico-amygdaloid projections of the rat occipital cortex: A Phaseolus vulgaris leucoagglutinin study. Neuroscience 71:37– 54.

MÉtin, C., Godement, P., and Imbert, M. (1988). The primary visual cortex in the mouse: Receptive field properties and functional organization. Exp. Brain Res. 69:594–612.

Meyer-Lindenberg, A., Kohn, P., Mervis, C. B., Kippenhan, J. S., Olsen, R. K., Morris, C. A., and Berman, K. F. (2004). Neural basis of genetically determined visuospatial construction deficit in Williams syndrome. Neuron 43:623–631.

Miller, M. W., and Vogt, B. A. (1984). Direct connections of rat visual cortex with sensory, motor, and association cortices. J. Comp. Neurol. 226:184–202.

Montero, V. M. (1993). Retinotopy of cortical connections between the striate cortex and extrastriate visual areas in the rat.

Exp. Brain Res. 94:1–15.

Neafsey, E. J. (1990). The complete ratunculus: Output organization of layer V of the cerebral cortex. In B. Kolb and R. C. Tees (Eds.), The cerebral cortex of the rat (pp. 197–212). Cambridge, MA: MIT Press.

Olavarria, J., Mignano, L. R., and Van Sluyters, R. C. (1982). Pattern of extrastriate visual areas connecting reciprocally with striate cortex in mouse. Exp. Neurol. 78:775–779.

Olavarria, J., and Montero, V. M. (1984). Relation of callosal and striate-extrastriate cortical connections in the rat: Morphological definition of extrastriate visual areas. Exp. Brain Res. 54:240–252.

Olavarria, J., and Montero, M. V. (1989). Organization of visual cortex in the mouse revealed by correlating callosal and striateextrastriate connections. Vis. Neurosci. 3:59–69.

Pang, J. J., Gao, F., and Wu, S. M. (2003). Light-evoked excitatory and inhibitory synaptic inputs to ON and OFF alpha ganglion cells in the mouse retina. J. Neurosci. 23:6063–6073.

Paxinos, G., and Franklin, K. B. J. (2001). The mouse brain in stereotaxic coordinates. New York: Academic Press.

Polleux, F., and Lauder, J. M. (2004). Toward a developmental neurobiology of autism. Ment. Retard. Dev. Dis. Res. Rev. 10: 303–317.

Prusky, G. T., Douglas, R. M., Nelson, L., Shabanpoor, A., and Sutherland, R. J. (2004). Visual memory task for rats reveals an essential role for hippocampus and perirhinal cortex. Proc. Natl. Acad. Sci. U.S.A. 101:5064–5068.

Roe, A. W. and Ts’o, D. Y. (1995). Visual topography in primate V2: Multiple representations across functional stripes. J. Neurosci. 15:3689–3715.

Rosa, M. G. P., and Krubitzer, L. A. (1999). The evolution of visual cortex: Where is V2? Trends Neurosci. 22:242–248.

Rose, M. (1912). Histologische Lokalisation der Grosshirnrinde bei kleinen Säugetieren (Rodentia, Insectivora, Chiroptera). J. Psychol. Neurol. 19:119–479.

Rose, M. (1929). Cytoarchitektonischer Atlas der Grosshirnrinde der Maus. J. Psychol. Neurol. 40:1–32.

Rumberger, A., Tyler, C. J., and Lund, J. S. (2001). Intraand inter-areal connections between the primary visual cortex V1 and the areas immediately surrounding V1 in the rat. Neuroscience 102:35–52.

Sanides, F., and Hoffman, J. (1969). Cytoand myeloarchitecture of the visual cortex of the cat and the surrounding integration cortices. J. Hirnforsch. 11:79–104.

Save, E., Paz-Villagran, V., Alexinsky, T., and Poucet, B. (2005). Functional interaction between the associative parietal cortex and hippocampal place cell firing in the rat. J. Eur. Neurosci. 21:522–530.

Schuett, S., Bonhoffer, T., and HÜbener, M. (2002). Mapping retinotopic structure in mouse visual cortex with optical imaging. J. Neurosci. 22:6549–6559.

SchÜz, A., Chaimov, D., Liewald, D., and Dortenman, M. (2006). Quantitative aspects of cortical connections: A tracer study in the mouse. Cereb. Cortex 16:1474–1486.

Simmons, P. A., Lemmon, V., and Pearlman, A. L. (1982). Afferent and efferent connections of the striate and extrastriate visual cortex of the normal and reeler mouse. J. Comp. Neurol. 211: 295–308.

Stone, C., and Pinto, L. H. (1993). Response properties of retinal ganglion cells in the isolated mouse retina. Vis. Neurosci. 10: 31–39.

Striedter, G. F. (2006). Principles of brain evolution. Sunderland, MA: Sinauer.

Sun, W., Li, N., and He, S. (2002). Large-scale morphological survey of mouse retinal ganglion cells. J. Comp. Neurol. 451: 115–126.

Taube, J. S. (1998). Head direction cells and the neurophysiological basis for a sense of direction. Prog. Neurobiol. 55:225–256.

Thomas, H. C., and Espinoza, S. G. (1987). Relationship between interhemispheric cortical connections and visual areas in hooded rats. Brain Res. 417:214–224.

Toldi, J., FehÉr, O., and Wolf, J. R. (1986). Sensory interactive zones in the rat cerebral cortex. Neuroscience 18:461–465.

Tsiola, A., Hamzei-Sichani, F., Peterlin, Z., and Yuste, R. (2003). Quantitative morphologic classification of layer 5 neurons from mouse primary visual cortex. J. Comp. Neurol. 461:415– 428.

Ungerleider, L. G., and Pasternak, T. (2004). Ventral and dorsal cortical processing streams. In L. M. Chalupa and J. S. Werner (Eds.), The visual neurosciences (pp. 541–562). Cambridge, MA: MIT Press.

Usrey, W. M., and Reid, R. C. (2000). Visual physiology and the lateral geniculate nucleus in two species of New World monkey:

Saimiri sciureus and Aotus trivirgatus. J. Physiol. 523.3:755–769. Valverde, F. (1968). Structural changes in the area striate of the

mouse after enucleation. Exp. Brain Res. 5:274–292.

Valverde, F. (1976). Aspects of cortical organization related to the geometry of neurons with intra-cortical axons. J. Neurocytol. 5:509–529.

Valverde, F., and EstÉban, E. (1968). Peristriate cortex of mouse: Location and the effects of enucleation on the number of dendritic spines. Brain Res. 9:145–148.

Van Essen, D. C. (1979). Visual areas of the mammalian cerebral cortex. Annu. Rev. Neurosci. 2:227–263.

Van Essen, D. C., Dierker, D., Snyder, A. Z., Raichle, M. E., Reiss, A. L., and Korenberg, J. (2006). Symmetry of cortical folding abnormalities in Williams syndrome revealed by surfacebased analyses. J. Neurosci. 26:5470–5483.

Van Essen, D. C., and Maunsell, J. H. R. (1981). The middle temporal visual area in the macaque: Myeloarchitecture, connections, functional properties and topographic organization. J. Comp Neurol. 199:293–326.

Van Hooser, S. D., Heimel, J. A., Chung., S., and Nelson, S. B. (2006). Lack of patchy horizontal connectivity in primary visual cortex of a mammal without orientation maps. J Neurosci. 26:7680–7692.

Van Hooser, S. D., Heimel, J. A., and Nelson, S. B. (2003). Receptive field properties and laminar organization of lateral geniculate nucleus in the gray squirrel (Sciurus carolensis). J. Neurophysiol. 90:3398–3418.

Wagor, E., Mangini, N. J., and Pearlman, A. L. (1980). Retinotopic organization of striate and extrastriate visual cortex in the mouse. J. Comp. Neurol. 193:187–202.

Wang, Q., and Burkhalter, A. (2003). Anatomical evidence for different processing streams in mouse visual cortex. Soc. Neurosci. Abstr. 701.3.

Wang, Q., and Burkhalter, A. (2004). Dorsal and ventral streams for processing of visual information in mouse cerebral cortex.

Soc. Neurosci. Abstr. 300.5.

Wang, Q., and Burkhalter, A. (2005). Separate output streams from V1 to higher areas of mouse visual cortex. Soc. Neurosci. Abstr. 854.1.

Wang, Q., and Burkhalter, A. (2007). Area map of mouse visual cortex. J. Comp. Neurol. 502(3):339–357.

Yamashita, A., Valkova., K., Gonchar., Y., and Burkhalter, A. (2003). Rearrangement of synaptic connections with inhibitory neurons in developing mouse visual cortex. J. Comp. Neurol. 464:426–437.

In this first era of genomic analysis of neural systems, the emphasis falls on what genes code, where particular genes are expressed, and what kinds of disorders appear when genes are mutated, absent, or misapplied. Less emphasis is placed on when and for how long genes are expressed, and less still on the control that coordinates the expression of ensembles of genes that construct developing sensory systems and brains. Control of the timing and duration of gene expression is certainly the major way in which vertebrate eyes differ from each other, because vertebrate eyes are quite conservative in their cell types, neurotransmitters, neuromodulators, and general structure (Rodieck, 1973; Arendt, 2003), with variation in opsins the notable exception (Shyue et al., 1995). The most significant differences in vertebrate eyes are in size, in the ratios of numbers of cell types, and in the arrangement of these cells. These differences suggest that alterations in the control of genes expressed, rather than the nature of the genes expressed, is the principal source of variation in evolution. Understanding the class of variations in developmental timing that can give rise to functional eyes should be a focus of genomic work as well. How the components of the eye are caused to scale gracefully and integrate with each other gives us a different way of approaching the genome than the more static version presented by the study of a single species.

The conservation of the constitutive elements of the eye, and of the visual system in general, is thus good and bad news for the mouse model. Because of the conservation, mechanistic comparability in most domains will be good. On the other hand, permissible and pathological variations in the duration and timing of gene expression are difficult to distinguish or characterize in an animal with such a relatively brief gestation period (ca. 18.5 days). The qualitative trait locus method of correlating variations in parameters such as brain size or gestational length with regions of the genome (e.g., Zhou and Williams, 1999) is a first step toward

integrating intraand interspecies variation with pathological variation. In addition, some natural variations in rapidly and slowly developing mice chimeras could be used to investigate basic questions about overarching control of rates of neurodevelopment (Williams and Goldowitz, 1992).

Understanding the chronology of development has an empirical aspect and a theoretical aspect. In this chapter, we first describe the chronology of development of the mouse visual system in relation to that in humans and monkeys, using a comprehensive model we and our colleagues have developed. This model capitalizes on the essential conservation of developmental timing in mammals for interspecies comparison and for interpolating missing data accurately in those cases where the data have not been or cannot be determined empirically (neurogenesis data, for example, require invasive techniques). This database is intended as a resource for the optimal developmental placement of any observation or experiment, as well as for investigating the control of developmental timing per se. We point out areas of greatest similarity between mice, other experimental animals, and humans that suggest the most reliable prediction, and also point out areas of difference that would make the mouse model less reliable. Finally, we suggest areas of investigation that would be particularly interesting to pursue in light of mouse and human similarities and differences in chronology.

Timetable of mouse development

Table 21.1 lists the observed and computed times of various visual developmental events in mouse, human, and rhesus macaque, all given in postconception (PC) days, where the day of conception is designated day zero. This table is excerpted from a much more extensive database that includes 102 events in early development (principally neurogenesis, tract formation, and structure innervation) from all sensory