Hostname: page-component-77f85d65b8-45ctf Total loading time: 0 Render date: 2026-04-17T16:12:48.582Z Has data issue: false hasContentIssue false
  • English
  • Français

Organization of the dorsal lateral geniculate nucleus in the mouse

Published online by Cambridge University Press:  10 August 2017

DANIEL KERSCHENSTEINER  and
WILLIAM GUIDO
DANIEL KERSCHENSTEINER*
Affiliation:
Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, Saint Louis, Missouri 63110 Department of Neuroscience, Washington University School of Medicine, Saint Louis, Missouri 63110 Department of Biomedical Engineering, Washington University School of Medicine, Saint Louis, Missouri 63110 Hope Center for Neurological Disorders, Washington University School of Medicine, Saint Louis, Missouri 63110
WILLIAM GUIDO*
Affiliation:
Department of Anatomical Sciences and Neurobiology, University of Louisville School of Medicine, Louisville, Kentucky 40292
*
*Address correspondence to: Daniel Kerschensteiner, Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO 63110. E-mail: kerschensteinerd@wustl.edu; William Guido, Department of Anatomical Sciences and Neurobiology, University of Louisville School of Medicine, 511 S. Floyd St, Louisville, KY 40292. E-mail: william.guido@louisville.edu
*Address correspondence to: Daniel Kerschensteiner, Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO 63110. E-mail: kerschensteinerd@wustl.edu; William Guido, Department of Anatomical Sciences and Neurobiology, University of Louisville School of Medicine, 511 S. Floyd St, Louisville, KY 40292. E-mail: william.guido@louisville.edu
Rights & Permissions [Opens in a new window]

Abstract

The dorsal lateral geniculate nucleus (dLGN) of the thalamus is the principal conduit for visual information from retina to visual cortex. Viewed initially as a simple relay, recent studies in the mouse reveal far greater complexity in the way input from the retina is combined, transmitted, and processed in dLGN. Here we consider the structural and functional organization of the mouse retinogeniculate pathway by examining the patterns of retinal projections to dLGN and how they converge onto thalamocortical neurons to shape the flow of visual information to visual cortex.

Keywords

VisionRetinogeniculate pathwayRetinal ganglion cellsThalamocortical neurons

Information

Type
Review Article
Information
Visual Neuroscience , Volume 34 , 2017 , E008
Copyright
Copyright © Cambridge University Press 2017 

Introduction

The dorsal lateral geniculate nucleus of the thalamus (dLGN) connects the retina to visual cortex. Early studies suggested that the retina sends signals to dLGN through the axons of relatively few retinal ganglion cell (RGC) types that carry parallel streams of visual information (Martin, Reference Martin1986). In dLGN, each thalamocortical neuron (TC) was reported to receive input from one or few RGCs (Levick et al., Reference Levick, Cleland and Dubin1972; Chen & Regehr, Reference Chen and Regehr2000; Hong et al., Reference Hong, Park, Litvina, Morales, Sanes and Chen2014), maintaining separation of the incoming channels. As a result, dLGN was thought to function as a relatively simple relay of retinal information to visual cortex (Hubel & Wiesel, Reference Hubel and Wiesel1961; Lee et al., Reference Lee, Virsu and Creutzfeldt1983; Tavazoie & Reid, Reference Tavazoie and Reid2000; Grubb & Thompson, Reference Grubb and Thompson2003). Recent studies, however, have revealed far greater diversity among RGC types (Field & Chichilnisky, Reference Field and Chichilnisky2007; Baden et al., Reference Baden, Berens, Franke, Roman Roson, Bethge and Euler2016), most of which send axons to dLGN (Dacey et al., Reference Dacey, Peterson, Robinson and Gamlin2003; Ellis et al., Reference Ellis, Gauvain, Sivyer and Murphy2016). In addition, anatomical circuit reconstructions demonstrated that convergence of RGC axons onto TCs is higher than previously thought (Hammer et al., Reference Hammer, Monavarfeshani, Lemon, Su and Fox2015; Morgan et al., Reference Morgan, Berger, Wetzel and Lichtman2016; Rompani et al., Reference Rompani, Mullner, Wanner, Zhang, Roth, Yonehara and Roska2017); and functional recordings uncovered diverse light responses among TCs (Marshel et al., Reference Marshel, Kaye, Nauhaus and Callaway2012; Piscopo et al., Reference Piscopo, El-Danaf, Huberman and Niell2013; Zhao et al., Reference Zhao, Chen, Liu and Cang2013a ). These studies have renewed interest in the functional organization of dLGN. Here, we discuss our current understanding of this organization from two sides: the projection patterns of RGC axons, and the diversity and distribution of TC neurons in dLGN. For the sake of clarity and brevity, we focus primarily on studies of mice.

The organization of RGC projections in mouse dLGN

The dLGN receives information about the outside world most directly from RGC axons, the terminations of which are organized into overlapping maps according to three criteria: (i) eye of origin (i.e., eye-specific segregation), (ii) topographic position within the retina (i.e., retinotopic map), and (iii) cell type (i.e., cell-type-specific lamination) (Fig. 1).

Fig. 1. Schematics illustrate the organization of mouse dLGN. (A) Pattern of projections for different RGC cell types. (B) Hidden lamination in mouse dLGN. Left: Eye specific patterning of retinal projections arising from the contralateral (green) and ipsilateral eye. Right: Shell (blue) and core (purple) subdivisions. The shell receives convergent input from DSGCs and the superficial layers of the superior colliculus. The core receives input largely from RGCs with a canonical center surround organization. (C) Dendritic architecture of different classes of relay neurons (X, Y, W) and interneurons along with their regional preferences within dLGN.

Eye-specific segregation of RGC axons in dLGN

In mice, as in other animals with laterally positioned eyes, the majority or RGC axons cross sides in the optic chiasm (Jaubert-Miazza et al., Reference Jaubert-Miazza, Green, Lo, Bui, Mills and Guido2005; Petros et al., Reference Petros, Rebsam and Mason2008; Dhande & Huberman, Reference Dhande and Huberman2014). Tracer injections showed that axons from contra- and ipsilateral eyes occupy nonoverlapping domains of the mature dLGN (Godement et al., Reference Godement, Salaun and Imbert1984; Reese, Reference Reese1988; Muir-Robinson et al., Reference Muir-Robinson, Hwang and Feller2002; Jaubert-Miazza et al., Reference Jaubert-Miazza, Green, Lo, Bui, Mills and Guido2005) (Fig. 1B). The small ipsilateral projection localizes to the medial dLGN, and is topographically aligned with the contralateral projection (Reese & Jeffery, Reference Reese and Jeffery1983; Reese, Reference Reese1988). During development, eye-specific segregation emerges gradually by refinement of initially overlapping axons (Godement et al., Reference Godement, Salaun and Imbert1984; Muir-Robinson et al., Reference Muir-Robinson, Hwang and Feller2002; Jaubert-Miazza et al., Reference Jaubert-Miazza, Green, Lo, Bui, Mills and Guido2005). Sparse labeling by in vivo electroporation revealed that at the level of single RGCs, refinement involves the elaboration of axon arbors prepositioned in the proper location and the elimination of inappropriately targeted sparse branches (Dhande et al., Reference Dhande, Hua, Guh, Yeh, Bhatt, Zhang, Ruthazer, Feller and Crair2011). Axonal refinement is instructed by spontaneous activity patterns (i.e., retinal waves), which synchronize the firing of RGCs in the same eye (Meister et al., Reference Meister, Wong, Baylor and Shatz1991; Ackman et al., Reference Ackman, Burbridge and Crair2012); and perturbations of retinal waves can block segregation and desegregate refined projections (Chapman, Reference Chapman2000; Stellwagen & Shatz, Reference Stellwagen and Shatz2002; Demas et al., Reference Demas, Sagdullaev, Green, Jaubert-Miazza, McCall, Gregg, Wong and Guido2006; Koch et al., Reference Koch, Dela Cruz, Hnasko, Edwards, Huberman and Ullian2011; Zhang et al., Reference Zhang, Ackman, Xu and Crair2011; Burbridge et al., Reference Burbridge, Xu, Ackman, Ge, Zhang, Ye, Zhou, Xu, Contractor and Crair2014). The initial positioning of RGC axons in dLGN is determined by molecular gradients of Ephs and ephrins (McLaughlin & O’Leary, Reference McLaughlin and O’Leary2005; Huberman et al., Reference Huberman, Manu, Koch, Susman, Lutz, Ullian, Baccus and Barres2008; Cang & Feldheim, Reference Cang and Feldheim2013); and, although spontaneous activity can still drive eye-specific segregation when Eph/ephrin signaling is perturbed, ipsilateral patches are fractured and mislocalized (Huberman et al., Reference Huberman, Murray, Warland, Feldheim and Chapman2005; Pfeiffenberger et al., Reference Pfeiffenberger, Cutforth, Woods, Yamada, Renteria, Copenhagen, Flanagan and Feldheim2005).

The small size of the ipsilateral projection (Jaubert-Miazza et al., Reference Jaubert-Miazza, Green, Lo, Bui, Mills and Guido2005; Coleman et al., Reference Coleman, Law and Bear2009) and the comparatively large size of TC dendritic arbors (Krahe et al., Reference Krahe, El-Danaf, Dilger, Henderson and Guido2011; Morgan et al., Reference Morgan, Berger, Wetzel and Lichtman2016), suggest that information from both eyes may converge in dLGN. A recent trans-synaptic tracing study showed that a subset of TC neurons receive input from both eyes (Rompani et al., Reference Rompani, Mullner, Wanner, Zhang, Roth, Yonehara and Roska2017). The extent and stimulus conditions under which binocular responses occur in dLGN are a topic of debate and ongoing investigation (Grubb et al., Reference Grubb, Rossi, Changeux and Thompson2003; Ziburkus & Guido, Reference Ziburkus and Guido2006; Zhao et al., Reference Zhao, Liu and Cang2013b ; Howarth et al., Reference Howarth, Walmsley and Brown2014) (see part II below).

Retinotopic map of RGC axons in dLGN

To preserve spatial information about the visual world, axons of neighboring RGCs project to neighboring places in dLGN, forming retinotopic maps (Reese & Jeffery, Reference Reese and Jeffery1983; Reese, Reference Reese1988; McLaughlin & O’Leary, Reference McLaughlin and O’Leary2005; Huberman et al., Reference Huberman, Manu, Koch, Susman, Lutz, Ullian, Baccus and Barres2008). Retinotopic order is maintained beyond dLGN along the ventral and dorsal streams of the visual system (Andermann et al., Reference Andermann, Kerlin, Roumis, Glickfeld and Reid2011; Marshel et al., Reference Marshel, Garrett, Nauhaus and Callaway2011; Wang et al., Reference Wang, Gao and Burkhalter2011; Roth et al., Reference Roth, Helmchen and Kampa2012; Wang et al., Reference Wang, Sporns and Burkhalter2012). Given the convergence of multiple RGCs onto a single TC neuron (Hong et al., Reference Hong, Park, Litvina, Morales, Sanes and Chen2014; Hammer et al., Reference Hammer, Monavarfeshani, Lemon, Su and Fox2015; Morgan et al., Reference Morgan, Berger, Wetzel and Lichtman2016), precise retinotopic mapping of RGC axons is required for contiguous high-acuity receptive fields in dLGN. In cats and ferrets, mature TC receptive fields emerge from spatially and functionally imprecise beginnings during a period of refinement (Tavazoie & Reid, Reference Tavazoie and Reid2000; Akerman et al., Reference Akerman, Grubb and Thompson2004). No data on the development of TC receptive fields in mice have been published, but anatomical studies indicate that topographic precision of RGC projections increases during the first two weeks of life (Dhande et al., Reference Dhande, Bhatt, Anishchenko, Elstrott, Iwasato, Swindell, Xu, Jamrich, Itohara, Feller and Crair2012). Similar to eye-specific segregation, retinotopic maps of RGC axons are established and refined by the combined action of Eph/ephrin gradients and activity-dependent plasticity (McLaughlin & O’Leary, Reference McLaughlin and O’Leary2005; Huberman et al., Reference Huberman, Manu, Koch, Susman, Lutz, Ullian, Baccus and Barres2008; Cang & Feldheim, Reference Cang and Feldheim2013; Xu et al., Reference Xu, Burbridge, Chen, Ge, Zhang, Zhou and Crair2015). When Eph/ephrin signaling is perturbed, projections from nearby RGCs are split, disrupting retinotopic order in dLGN (Pfeiffenberger et al., Reference Pfeiffenberger, Yamada and Feldheim2006). By contrast, termination zones of RGC axons remain appropriately localized but broaden when spontaneous activity patterns are perturbed (Grubb et al., Reference Grubb, Rossi, Changeux and Thompson2003; Burbridge et al., Reference Burbridge, Xu, Ackman, Ge, Zhang, Ye, Zhou, Xu, Contractor and Crair2014) widening TC receptive fields (Grubb et al., Reference Grubb, Rossi, Changeux and Thompson2003; Cang et al., Reference Cang, Niell, Liu, Pfeiffenberger, Feldheim and Stryker2008).

Cell-type-specific lamination of RGC axons in dLGN

Morphological and functional surveys, and an increasing number of transgenic mouse lines reveal extraordinary diversity among RGCs, which comprise 30–40 distinct cell types in mice (Sun et al., Reference Sun, Li and He2002; Badea & Nathans, Reference Badea and Nathans2004; Coombs et al., Reference Coombs, van der List, Wang and Chalupa2006; Helmstaedter et al., Reference Helmstaedter, Briggman, Turaga, Jain, Seung and Denk2013; Sumbul et al., Reference Sumbul, Song, McCulloch, Becker, Lin, Sanes, Masland and Seung2014; Sanes & Masland, Reference Sanes and Masland2015; Baden et al., Reference Baden, Berens, Franke, Roman Roson, Bethge and Euler2016). Retrograde labeling indicates that most of these RGCs project to dLGN in mice (Ellis et al., Reference Ellis, Gauvain, Sivyer and Murphy2016), as they do in primates (Dacey et al., Reference Dacey, Peterson, Robinson and Gamlin2003), suggesting that a large number of parallel information streams enter dLGN. To what extent incoming streams remain separate, or how their information is combined by TCs depends in part on the cell-type-specific projection patterns of RGC axons in dLGN (Fig. 1).

In primates, cats, and ferrets, dLGN neurons are separated into distinct cellular layers that receive input from specific RGC types (Usrey & Alitto, Reference Usrey and Alitto2015); whereas in mouse and rat, dLGN neurons show no apparent separation (Reese, Reference Reese1988; Usrey & Alitto, Reference Usrey and Alitto2015). Yet, RGC axons impose order on these comparatively unorganized targets by arborizing in cell-type-specific patterns (Fig. 1A). Early tracing studies hinted at lamination of RGC axons in rats (Reese, Reference Reese1988). This organization is now being revealed in increasing detail by a growing number of transgenic mouse lines that label specific subsets or individual types of RGCs (Siegert et al., Reference Siegert, Scherf, Del Punta, Didkovsky, Heintz and Roska2009; Hong et al., Reference Hong, Park, Litvina, Morales, Sanes and Chen2014; Dhande et al., Reference Dhande, Stafford, Lim and Huberman2015; Sanes & Masland, Reference Sanes and Masland2015). In addition to studies of individual mouse lines, the Allen Mouse Brain Connectivity Atlas includes adeno-associated virus (AAV) tracing studies of projections from RGCs labeled in a variety of Cre-driver lines (http://connectivity.brain-map.org/). A summary of this effort was recently published (Martersteck et al., Reference Martersteck, Hirokawa, Evarts, Bernard, Duan, Li, Ng, Oh, Ouellette, Royall, Stoecklin, Wang, Zeng, Sanes and Harris2017).

The mouse retina contains a large number of direction selective ganglion cell (DSGC) types (Borst & Euler, Reference Borst and Euler2011; Sanes & Masland, Reference Sanes and Masland2015). Among these, two canonical groups are distinguished by their contrast preferences: ON-DSGCs respond to light increments and ON–OFF DSGCs respond to light increments and decrements (Borst & Euler, Reference Borst and Euler2011; Sanes & Masland, Reference Sanes and Masland2015). ON-DSGCs prefer motion in one of three directions that are aligned with the orientation of the semicircular canals in the inner ear (Yonehara et al., Reference Yonehara, Ishikane, Sakuta, Shintani, Nakamura-Yonehara, Kamiji, Usui and Noda2009; Dhande et al., Reference Dhande, Estevez, Quattrochi, El-Danaf, Nguyen, Berson and Huberman2013). ON-DSGCs largely avoid dLGN, project to brainstem nuclei of the accessory optic system, and, together with the vestibular system, drive image stabilizing eye movements (Simpson, Reference Simpson1984; Yonehara et al., Reference Yonehara, Ishikane, Sakuta, Shintani, Nakamura-Yonehara, Kamiji, Usui and Noda2009; Dhande et al., Reference Dhande, Estevez, Quattrochi, El-Danaf, Nguyen, Berson and Huberman2013; Gauvain & Murphy, Reference Gauvain and Murphy2015; Osterhout et al., Reference Osterhout, Stafford, Nguyen, Yoshihara and Huberman2015; Sun et al., Reference Sun, Brady, Cahill, Al-Khindi, Sakuta, Dhande, Noda, Huberman, Nathans and Kolodkin2015). ON–OFF DSGCs prefer motion in one of four cardinal directions (nasal, temporal, dorsal, or ventral) (Borst & Euler, Reference Borst and Euler2011; Sanes & Masland, Reference Sanes and Masland2015). More than one cell type may exist for each preferred direction (Rivlin-Etzion et al., Reference Rivlin-Etzion, Zhou, Wei, Elstrott, Nguyen, Barres, Huberman and Feller2011; Baden et al., Reference Baden, Berens, Franke, Roman Roson, Bethge and Euler2016); and all ON–OFF DSGC types examined so far project to the ventricular margin of the dLGN, also known as the dLGN shell (Huberman et al., Reference Huberman, Wei, Elstrott, Stafford, Feller and Barres2009; Kim et al., Reference Kim, Zhang, Meister and Sanes2010; Kay et al., Reference Kay, De la Huerta, Kim, Zhang, Yamagata, Chu, Meister and Sanes2011; Rivlin-Etzion et al., Reference Rivlin-Etzion, Zhou, Wei, Elstrott, Nguyen, Barres, Huberman and Feller2011) (Fig. 1A and 1B). Their projection patterns are not uniform, however, as axon arbors of ventral motion preferring ON–OFF DSGCs also cover an adjacent layer in the dLGN core (Kim et al., Reference Kim, Zhang, Meister and Sanes2010; Kay et al., Reference Kay, De la Huerta, Kim, Zhang, Yamagata, Chu, Meister and Sanes2011). Interestingly, TCs in the dLGN shell and core project to different layers of visual cortex (layers 1 and 2 vs., layer 4, respectively) indicating that RGCs projecting to the respective areas participate in separate visual pathways (Grubb & Thompson, Reference Grubb and Thompson2004; Cruz-Martin et al., Reference Cruz-Martin, El-Danaf, Osakada, Sriram, Dhande, Nguyen, Callaway, Ghosh and Huberman2014; Bickford et al., Reference Bickford, Zhou, Krahe, Govindaiah and Guido2015). ON–OFF DSGCs target the dLGN shell before eye opening (Kay et al., Reference Kay, De la Huerta, Kim, Zhang, Yamagata, Chu, Meister and Sanes2011; Osterhout et al., Reference Osterhout, El-Danaf, Nguyen and Huberman2014) by mechanisms that remain to be uncovered, and maintain their laminar position independent of spontaneous and sensory-evoked activity patterns (Soto et al., Reference Soto, Ma, Cecil, Vo, Culican and Kerschensteiner2012).

Recently, three noncanonical DSGC types (J-, F-miniON-, and F-miniOFF-RGCs) were identified based on gene expression patterns, and characterized in two transgenic mouse lines (Kim et al., Reference Kim, Zhang, Yamagata, Meister and Sanes2008; Joesch & Meister, Reference Joesch and Meister2016; Rousso et al., Reference Rousso, Qiao, Kagan, Yamagata, Palmiter and Sanes2016). These noncanonical DSGCs have asymmetric dendritic arbors and uniformly prefer ventral motion (Kim et al., Reference Kim, Zhang, Yamagata, Meister and Sanes2008; Rousso et al., Reference Rousso, Qiao, Kagan, Yamagata, Palmiter and Sanes2016). Dendrites of noncanonical DSGCs stratify outside the ChAT (i.e., cholineacetyltransferase) bands formed by neurites of starburst amacrine cells, which are critical for canonical direction selective responses in the retina (Borst & Euler, Reference Borst and Euler2011). Although the circuit mechanisms underlying their response selectivity therefore likely differ from those of canonical DSGCs, the axons of J- and F-miniON- and F-miniOFF-RGCs similarly target the dLGN shell (Kay et al., Reference Kay, De la Huerta, Kim, Zhang, Yamagata, Chu, Meister and Sanes2011; Rousso et al., Reference Rousso, Qiao, Kagan, Yamagata, Palmiter and Sanes2016) (Fig. 1A and 1B).

Patch clamp recordings from large somata in the ganglion cell layer of the retina led to the characterization of three RGC types: one responds with sustained firing to light increments (ONS-RGCs), another responds with sustained firing to light decrements (OFFS-RGC), and the third responds transiently to light decrements (OFFT-RGC) (Murphy & Rieke, Reference Murphy and Rieke2006). Based on morphological and functional homology to RGC types in cats, these cells are also referred to as ONα (ONS), OFFδ (OFFS), and OFFα (OFFT) (Pang et al., Reference Pang, Gao and Wu2003; Park et al., Reference Park, Borghuis, Rahmani, Zeng, Kim and Demb2015). OFFT-RGCs were one of the first genetically identified RGC types (CB2-EGFP mice), whose central projections were mapped (Huberman et al., Reference Huberman, Manu, Koch, Susman, Lutz, Ullian, Baccus and Barres2008). Since then, different combinations ONS-, OFFS-, and OFFT-RGCs have been found to be labeled in a number of transgenic mouse lines (Ecker et al., Reference Ecker, Dumitrescu, Wong, Alam, Chen, LeGates, Renna, Prusky, Berson and Hattar2010; Farrow et al., Reference Farrow, Teixeira, Szikra, Viney, Balint, Yonehara and Roska2013; Bleckert et al., Reference Bleckert, Schwartz, Turner, Rieke and Wong2014; Duan et al., Reference Duan, Krishnaswamy, De la Huerta and Sanes2014). Results from the initial characterizations of these mice and from the Allen Brain Connectivity Atlas, suggest that ONS-, OFFS-, and OFFT-RGCs project to medial aspects of the dLGN core (Fig. 1A and 1B). This conclusion is further supported by retrograde and trans-synaptic viral labeling studies, and by the preponderance of ONS, OFFS, and OFFT responses in the core of the dLGN (Piscopo et al., Reference Piscopo, El-Danaf, Huberman and Niell2013; Cruz-Martin et al., Reference Cruz-Martin, El-Danaf, Osakada, Sriram, Dhande, Nguyen, Callaway, Ghosh and Huberman2014; Ellis et al., Reference Ellis, Gauvain, Sivyer and Murphy2016).

Among the transgenic mice that label ONS-RGCs is Opn4-Cre, a line in which Cre recombinase is expressed from the Opn4 (i.e., melanopsin) locus (Ecker et al., Reference Ecker, Dumitrescu, Wong, Alam, Chen, LeGates, Renna, Prusky, Berson and Hattar2010; Schmidt et al., Reference Schmidt, Alam, Chen, Kofuji, Li, Prusky and Hattar2014). Melanopsin mediates light responses in a subset of RGCs, referred to collectively as intrinsically photosensitive RGCs (ipRGCs) (Provencio et al., Reference Provencio, Rodriguez, Jiang, Hayes, Moreira and Rollag2000; Berson et al., Reference Berson, Dunn and Takao2002; Hattar et al., Reference Hattar, Liao, Takao, Berson and Yau2002). A number of different ipRGC types have been distinguished (M1–M4) (Tu et al., Reference Tu, Zhang, Demas, Slutsky, Provencio, Holy and Van Gelder2005; Ecker et al., Reference Ecker, Dumitrescu, Wong, Alam, Chen, LeGates, Renna, Prusky, Berson and Hattar2010; Schmidt et al., Reference Schmidt, Chen and Hattar2011; Estevez et al., Reference Estevez, Fogerson, Ilardi, Borghuis, Chan, Weng, Auferkorte, Demb and Berson2012). All ipRGCs receive synaptic input from the retinal circuitry in addition to their intrinsic responses. The strengths of synaptic and intrinsic inputs appear to be inversely proportional and vary between ipRGC types, with M1 ipRGCs showing the strongest intrinsic responses and ONS-RGCs (i.e., M4 ipRGCs) showing the weakest intrinsic responses (Wong et al., Reference Wong, Dunn, Graham and Berson2007; Schmidt & Kofuji, Reference Schmidt and Kofuji2009; Estevez et al., Reference Estevez, Fogerson, Ilardi, Borghuis, Chan, Weng, Auferkorte, Demb and Berson2012; Schmidt et al., Reference Schmidt, Alam, Chen, Kofuji, Li, Prusky and Hattar2014). M1–M3 ipRGCs project to numerous subcortical visual areas, but avoid dLGN (Hattar et al., Reference Hattar, Kumar, Park, Tong, Tung, Yau and Berson2006), whereas ONS-RGCs (i.e., M4 ipRGCs) project to the dLGN core (Ecker et al., Reference Ecker, Dumitrescu, Wong, Alam, Chen, LeGates, Renna, Prusky, Berson and Hattar2010) (Fig. 1A and 1B). In addition to this direct pathway, melanopsin-mediated light responses regulate visual signals in dLGN through intraretinal influences of ipRGCs (Zhang et al., Reference Zhang, Wong, Sollars, Berson, Pickard and McMahon2008; Brown et al., Reference Brown, Gias, Hatori, Keding, Semo, Coffey, Gigg, Piggins, Panda and Lucas2010; Allen et al., Reference Allen, Storchi, Martial, Petersen, Montemurro, Brown and Lucas2014; Schmidt et al., Reference Schmidt, Alam, Chen, Kofuji, Li, Prusky and Hattar2014; Reifler et al., Reference Reifler, Chervenak, Dolikian, Benenati, Li, Wachter, Lynch, Demertzis, Meyers, Abufarha, Jaeckel, Flannery and Wong2015; Prigge et al., Reference Prigge, Yeh, Liou, Lee, You, Liu, McNeill, Chew, Hattar, Chen and Zhang2016).

RGCs are often broadly divided into ON, OFF, and ON–OFF groups, based on whether their firing rate increases in response to light increments, decrements, or both. However, one (or several) RGC type(s) does not fit into this classification scheme, and instead exhibits high baseline firing rates that are suppressed by ON and OFF stimuli. These cells are conserved from rodents to primates and are referred to as Suppressed-by-Contrast (SbC-) RGCs or uniformity detectors (Levick, Reference Levick1967; Rodieck, Reference Rodieck1967; de Monasterio, Reference de Monasterio1978; Sivyer et al., Reference Sivyer, Taylor and Vaney2010; Tien et al., Reference Tien, Pearson, Heller, Demas and Kerschensteiner2015). With the help of transgenic mice, the circuit mechanisms underlying the suppressive responses of SbC-RGCs are being worked out (Jacoby et al., Reference Jacoby, Zhu, DeVries and Schwartz2015; Tien et al., Reference Tien, Pearson, Heller, Demas and Kerschensteiner2015; Lee et al., Reference Lee, Zhang, Chen and Zhou2016; Tien et al., Reference Tien, Kim and Kerschensteiner2016). Unfortunately, no line so far labels SbC-RGCs exclusively, and their central projection patterns therefore remain somewhat uncertain. Nonetheless, two transgenic mouse lines that cover SbC-RGCs show strong projections to the dLGN core (Ivanova et al., Reference Ivanova, Lee and Pan2013; Zhu et al., Reference Zhu, Xu, Hauswirth and DeVries2014), and SbC responses have been recorded in dLGN and V1 (Niell & Stryker, Reference Niell and Stryker2010; Piscopo et al., Reference Piscopo, El-Danaf, Huberman and Niell2013) (Fig. 1A and 1B). Together these findings suggest that signals from SbC-RGCs may propagate along a dedicated retino-geniculo-cortical pathway. Alternatively, SbC signals could be generated by different mechanisms at subsequent stages of the visual system, similar to orientation selective (OS) responses (Niell, Reference Niell2013).

In spite of the recent progress, the projection patterns of many RGC types are still unknown. In addition to providing a more comprehensive picture of cell-type-specific lamination, future work will further elucidate what retinal information is excluded from dLGN. In addition to ON-DSGCs and M1–M3 ipRGCs, a recent study comparing functional properties of RGCs retrogradely labeled from dLGN and superior colliculus (SC), indicates that, although a majority of cells project to both targets, several RGC types that respond transiently and selectively to small stimuli avoid dLGN (Ellis et al., Reference Ellis, Gauvain, Sivyer and Murphy2016).

The organization of mouse dLGN

In mouse, the dLGN is a bean-shaped nucleus that resides in the dorsal lateral aspect of thalamus. In Nissl stained material, it is a homogenous structure with cytoarchitectural boundaries that separate it from the ventral basal complex, the intrageniculate leaflet, and ventral geniculate nuclei. As discussed above, “hidden laminae” exist in the form of eye specific retinal terminal domains, and as a shell and core region (Fig. 1B). The shell occupies a small strip of dLGN parallel to and just beneath the optic tract that receives input exclusively from the contralateral eye. The much larger core division lies beneath the shell, and receives input from both eyes, with those from the ipsilateral eye forming a small nonoverlapping, patchy cylinder that courses through the antero-medial region of the core. As discussed above, the shell and core receive input from distinct classes of RGCs (Fig. 1A and 1B). The shell is the primary recipient domain for many types of DSGCs, while the core harbors a diverse group of RGC input that in the aggregate appear to mediate canonical aspects of spatial vision (Dhande & Huberman, Reference Dhande and Huberman2014) (Fig. 1A and 1B). Additionally, the shell receives strong, excitatory input from superficial layers of SC, and together with input from DSGCs is believed to form a highly specialized visual channel that conveys information about stimulus motion and eye position to the superficial layers of visual cortex (Cruz-Martin et al., Reference Cruz-Martin, El-Danaf, Osakada, Sriram, Dhande, Nguyen, Callaway, Ghosh and Huberman2014; Bickford et al., Reference Bickford, Zhou, Krahe, Govindaiah and Guido2015). Indeed, the shell of mouse dLGN shares many of the same features noted in the C-laminae of carnivores and the koniocellular division of some primates (Demeulemeester et al., Reference Demeulemeester, Arckens, Vandesande, Orban, Heizmann and Pochet1991; Harting et al., Reference Harting, Huerta, Hashikawa and van Lieshout1991).

Neuronal cell types of dLGN

The neuronal composition of mouse dLGN is similar to that of other mammals (Parnavelas et al., Reference Parnavelas, Mounty, Bradford and Lieberman1977; Sherman & Guillery, Reference Sherman and Guillery2002). There are two principal cell types, thalamocortical relay cells (TC) and interneurons (Fig. 1C). In rodents, roughly 90% of all cells in dLGN are TC neurons, and the remainder interneurons (Arcelli et al., Reference Arcelli, Frassoni, Regondi, De Biasi and Spreafico1997). Both cell types receive retinal input, but only TC neurons have axons that exit the dLGN and project to the visual areas of cortex (Fig. 2). Ascending axons of TC neurons also have collaterals that terminate in the thalamic reticular nucleus, a shell-like structure comprised of GABAergic inhibitory neurons that surrounds the dorsal thalamus (Pinault, Reference Pinault2004). TC neurons make excitatory connections with TRN neurons, which in turn provide feedback inhibition onto TC neurons. Intrinsic interneurons have processes that are restricted to dLGN and form feedforward inhibitory connections with TC neurons (Fig. 2). A more detailed explanation of these inhibitory circuits and underlying synaptic arrangements can be found in accompanying review by Cox.

Fig. 2. Circuit diagram that depicts retinal (red) and nonretinal (blue) connections of intrinsic interneurons and thalamocortical relay neurons of mouse dLGN.

The morphology of neurons in the rodent LGN has been examined in Golgi impregnated material (Rafols & Valverde, Reference Rafols and Valverde1973; Parnavelas et al., Reference Parnavelas, Mounty, Bradford and Lieberman1977), and more recently in mouse from single cell intracellular fills performed during in vitro recording experiments (Jaubert-Miazza et al., Reference Jaubert-Miazza, Green, Lo, Bui, Mills and Guido2005; Krahe et al., Reference Krahe, El-Danaf, Dilger, Henderson and Guido2011; Seabrook et al., Reference Seabrook, Krahe, Govindaiah and Guido2013; El-Danaf et al., Reference El-Danaf, Krahe, Dilger, Bickford, Fox and Guido2015). Overall, TC neurons have a thick unbranched axon, large round soma, and complex multipolar dendritic arbors, whereas interneurons have a fusiform shaped soma and just a few sinuous dendritic processes. 3-D reconstructions of the dendritic architecture of TC neurons show they can be grouped into three distinct morphological classes that bear a striking resemblance to X (bi-conical), Y (symmetrical), and W (hemispheric) cells of the cat (Friedlander et al., Reference Friedlander, Lin, Stanford and Sherman1981; Stanford et al., Reference Stanford, Friedlander and Sherman1981, Reference Stanford, Friedlander and Sherman1983; Krahe et al., Reference Krahe, El-Danaf, Dilger, Henderson and Guido2011) (Fig. 1C). Additionally, each class exhibits a regional preference within dLGN (Krahe et al., Reference Krahe, El-Danaf, Dilger, Henderson and Guido2011). X cells are confined to the monocularly innervated, ventral region of dLGN. Y cells are found in the binocularly innervated central core region, and in some instances exhibit dendritic fields that extend into areas innervated by the contralateral and ipsilateral eye. W cells reside along the outer perimeter, and exclusively in the shell (Bickford et al., Reference Bickford, Zhou, Krahe, Govindaiah and Guido2015). These regional preferences are consistent with earlier studies in the rat, suggesting dLGN is organized into three separate retino-recipient domains; a central core that receives input from large, fast-conducting RGCs, an outer dorsal shell that receives input from small, slowly conducting RGCs and a ventral region for subset of smaller type RGCs (Martin, Reference Martin1986; Reese, Reference Reese1988). How these regional preferences and receptive field properties of X, Y, and W correspond to the projection streams of identified RCC cell types remains unclear (see below).

Similar 3-D reconstructions of interneurons do not reveal any subclass distinctions, although two classes may exist based on differences in their intrinsic membrane properties (Leist et al., Reference Leist, Datunashvilli, Kanyshkova, Zobeiri, Aissaoui, Cerina, Romanelli, Pape and Budde2016). Unlike TC neurons, interneurons are evenly dispersed throughout dLGN and have dendrites that readily cross eye-specific domains (Seabrook et al., Reference Seabrook, Krahe, Govindaiah and Guido2013) (Fig. 1C).

The degree and nature of retinal convergence onto TC neurons has been a topic of intense investigation. Studies in different species including mouse, reveal that retinal input onto dLGN neurons comprise about 10% of the total number of synapses in dLGN, with roughly 90% arising from a variety of nonretinal sources including layer V1 of visual cortex, brainstem cholinergic nuclei, and the thalamic reticular nucleus (Sherman & Guillery, Reference Sherman and Guillery2002; Sherman, Reference Sherman2004; Bickford et al., Reference Bickford, Slusarczyk, Dilger, Krahe, Kucuk and Guido2010) (Fig. 2). Despite this disparity, retinal terminals provide the primary excitatory drive for TC neurons, forming multiple contacts on proximal regions of TC dendrites (Hamos et al., Reference Hamos, Van Horn, Raczkowski and Sherman1987). In mouse, estimates of retinal convergence derived from in vitro slice recordings reveal that at early postnatal ages developing TC neurons receive relatively weak synaptic input from several RGCs, and during the first few weeks of postnatal life then undergo a substantial pruning to ultimately receive strong input from just a few (Guido, Reference Guido2008; Hong & Chen, Reference Hong and Chen2011). By contrast, interneurons do not go through a pruning period, but instead retain a relatively high level of retinal convergence into adulthood (Seabrook et al., Reference Seabrook, Krahe, Govindaiah and Guido2013), a feature that is consistent with their unique electronic structure and the synaptic arrangements they have with TC neurons (Sherman, Reference Sherman2004) (see accompanying review by Cox).

The degree of retinal convergence onto mouse TC neurons has been challenged by recent ultrastructural and trans-synaptic tracing studies, suggesting that an individual TC neuron can receive far more inputs than estimated using electrophysiological criteria (Hammer et al., Reference Hammer, Monavarfeshani, Lemon, Su and Fox2015; Morgan et al., Reference Morgan, Berger, Wetzel and Lichtman2016; Rompani et al., Reference Rompani, Mullner, Wanner, Zhang, Roth, Yonehara and Roska2017) (see accompanying review by Morgan). Using innovative trans-synaptic tracing techniques, Rompani et al. (Reference Rompani, Mullner, Wanner, Zhang, Roth, Yonehara and Roska2017) analyzed the number and type of RGCs innervating individual TC neurons. Among the 25 TC neurons analyzed, three modes of convergence were found; a relay mode where a given TC neuron receives monocular input from 1–5 RGCs of the same type, a combination mode where a TC neuron receives monocular input from 6–36 RGCs of different types, and a binocular mode where up 90 inputs of many different types from both eyes converge onto a single TC neuron. How these diverse patterns of convergence relate to receptive field properties of TC neurons and the nature of information transfer to visual cortex remains an open question. While these anatomical and physiological approaches provide somewhat discrepant results, they raise interesting questions about the relationship between form (ultrastructural) and function. One intriguing possibility is that only a few retinal inputs provide the excitatory drive for a TC neuron, while many others remain nascent, perhaps fluctuating in synaptic strength based on postnatal age or the quality of visual experience (Chen et al., Reference Chen, Bickford and Hirsch2016). As discussed below, whether TC neurons receive input from just a few or many RGCs, like carnivores and primates, their receptive field properties in many instances appear driven by a single RGC type.

Receptive field properties of dLGN neurons

Generally speaking, most dLGN neurons in mouse have large receptive fields (center diameter of 10–20 deg), summate information in a linear manner, and have a center-surround organization with an RF center that responds either in a sustained or transient manner to stimulus onset (ON) or offset (OFF) (Grubb & Thompson, Reference Grubb and Thompson2003; Piscopo et al., Reference Piscopo, El-Danaf, Huberman and Niell2013; Denman & Contreras, Reference Denman and Contreras2016; Durand et al., Reference Durand, Iyer, Mizuseki, de Vries, Mihalas and Reid2016; Suresh et al., Reference Suresh, Ciftcioglu, Wang, Lala, Ding, Smith, Sommer and Hirsch2016; Tang et al., Reference Tang, Ardila Jimenez, Chakraborty and Schultz2016). Sustained ON and OFF responses are encountered more frequently than transient ones, with the latter restricted to OFF responses (Piscopo et al., Reference Piscopo, El-Danaf, Huberman and Niell2013; Tang et al., Reference Tang, Ardila Jimenez, Chakraborty and Schultz2016). In mouse, dLGN neurons have poor spatial resolution (0.01–0.05 c/d), and respond optimally to relatively low temporal frequencies (1–4 Hz) (Grubb & Thompson, Reference Grubb and Thompson2003; Piscopo et al., Reference Piscopo, El-Danaf, Huberman and Niell2013; Durand et al., Reference Durand, Iyer, Mizuseki, de Vries, Mihalas and Reid2016; Tang et al., Reference Tang, Ardila Jimenez, Chakraborty and Schultz2016). In addition to these somewhat classical dLGN response properties, mouse dLGN neurons display a rather rich and diverse repertoire of unconventional properties. Most notable is the prevalence of responses that show a strong selectivity for one direction (direction selectivity, DS) or to two opposing directions (orientation selective, OS) of a moving stimulus (Marshel et al., Reference Marshel, Kaye, Nauhaus and Callaway2012; Piscopo et al., Reference Piscopo, El-Danaf, Huberman and Niell2013; Scholl et al., Reference Scholl, Tan, Corey and Priebe2013; Zhao et al., Reference Zhao, Chen, Liu and Cang2013a ). These DS/OS responses have broad tuning profiles along the four cardinal axes, remain unaffected by the removal of corticofugal input, and tend to cluster in the dorsal shell, the target recipient zone for many ON–OFF DSGCs (Fig. 1A and 1B). Another unusual property of some dLGN neurons is their ability to signal the absence of contrast in a visual scene (Piscopo et al., Reference Piscopo, El-Danaf, Huberman and Niell2013; Suresh et al., Reference Suresh, Ciftcioglu, Wang, Lala, Ding, Smith, Sommer and Hirsch2016; Piscopo et al., Reference Piscopo, El-Danaf, Huberman and Niell2013; Suresh et al., Reference Suresh, Ciftcioglu, Wang, Lala, Ding, Smith, Sommer and Hirsch2016). Such a response profile is similar to that of suppressed by contrast RGCs, showing a decreased firing to either the onset or offset of a visual stimulus (Tien et al., Reference Tien, Pearson, Heller, Demas and Kerschensteiner2015).

Arguably, one of the unique properties of mouse dLGN neurons reported falls outside the realm of image encoding. Using chromatic visual stimuli to activate RGCs that contain the photopigment melanopsin (ipRGCs), it was shown that up to 40% of dLGN neurons respond to whole-field ambient light steps, thereby acting as irradiance detectors (Brown et al., Reference Brown, Gias, Hatori, Keding, Semo, Coffey, Gigg, Piggins, Panda and Lucas2010). Irradiant responses in dLGN could possibly originate from core projecting, intrinsically photo-sensitive ON alpha RGCs (i.e., M4 ipRGCs) (Brown et al., Reference Brown, Gias, Hatori, Keding, Semo, Coffey, Gigg, Piggins, Panda and Lucas2010; Ecker et al., Reference Ecker, Dumitrescu, Wong, Alam, Chen, LeGates, Renna, Prusky, Berson and Hattar2010; Schmidt et al., Reference Schmidt, Alam, Chen, Kofuji, Li, Prusky and Hattar2014) but a direct link between this RGC cell type and melanopsin signaling in dLGN is lacking (Fig. 1A and 1B).

There is a consensus that in rodents, dLGN neurons are monocularly driven largely through the contralateral eye (Reese, Reference Reese1988; Grubb & Thompson, Reference Grubb and Thompson2003). However of notable exception is one report that provides evidence for a high incidence of binocular responses among mouse dLGN neurons (Howarth et al., Reference Howarth, Walmsley and Brown2014). These authors found little evidence to support monocular responses driven through the ipsilateral eye, but instead encountered many neurons with a response profile modulated by bright visual stimuli presented to the ipsilateral eye. A recent trans-synaptic labeling study provides additional support, suggesting that dLGN neurons residing in the binocular segment receive multiple inputs from both eyes (Rompani et al., Reference Rompani, Mullner, Wanner, Zhang, Roth, Yonehara and Roska2017). The robust binocular responses recorded in mouse dLGN are in stark contrast to the weak polysynaptic, non-dominate eye influences reported in cat and primates (Marrocco & McClurkin, Reference Marrocco and McClurkin1979; Guido et al., Reference Guido, Tumosa and Spear1989), and perhaps represent an emergent property unique to the rodent (Grieve, Reference Grieve2005; Zhao et al., Reference Zhao, Liu and Cang2013b ). Certainly, the small ipsilateral terminal domain and large dendritic arbor of Y cells located in the core provide a potential substrate for direct monosynaptic convergence (Fig. 1), but the full extent and the stimulus conditions that underlie binocular responsiveness wait further testing.

Acknowledgments

We thank T. Krahe for his assistance in the design of Fig. 1. This work was supported by NIH EY023341 (DK), EY026978 (DK), EY027411 (DK), and EY 012716 (WG).

References

Ackman, J.B., Burbridge, T.J. & Crair, M.C. (2012). Retinal waves coordinate patterned activity throughout the developing visual system. Nature 490, 219–225.CrossRefGoogle ScholarPubMed
Akerman, C.J., Grubb, M.S. & Thompson, I.D. (2004). Spatial and temporal properties of visual responses in the thalamus of the developing ferret. Journal of Neuroscience 24, 170–182.CrossRefGoogle ScholarPubMed
Allen, A.E., Storchi, R., Martial, F.P., Petersen, R.S., Montemurro, M.A., Brown, T.M. & Lucas, R.J. (2014). Melanopsin-driven light adaptation in mouse vision. Current Biology 24, 2481–2490.CrossRefGoogle ScholarPubMed
Andermann, M.L., Kerlin, A.M., Roumis, D.K., Glickfeld, L.L. & Reid, R.C. (2011). Functional specialization of mouse higher visual cortical areas. Neuron 72, 1025–1039.Google Scholar
Arcelli, P., Frassoni, C., Regondi, M.C., De Biasi, S. & Spreafico, R. (1997). GABAergic neurons in mammalian thalamus: A marker of thalamic complexity? Brain Research Bulletin 42, 27–37.Google Scholar
Badea, T.C. & Nathans, J. (2004). Quantitative analysis of neuronal morphologies in the mouse retina visualized by using a genetically directed reporter. Journal of Comparative Neurology 480, 331–351.CrossRefGoogle ScholarPubMed
Baden, T., Berens, P., Franke, K., Roman Roson, M., Bethge, M. & Euler, T. (2016). The functional diversity of retinal ganglion cells in the mouse. Nature 529, 345–350.Google Scholar
Berson, D.M., Dunn, F.A. & Takao, M. (2002). Phototransduction by retinal ganglion cells that set the circadian clock. Science 295, 1070–1073.Google Scholar
Bickford, M.E., Slusarczyk, A., Dilger, E.K., Krahe, T.E., Kucuk, C. & Guido, W. (2010). Synaptic development of the mouse dorsal lateral geniculate nucleus. Journal of Comparative Neurology 518, 622–635.Google Scholar
Bickford, M.E., Zhou, N., Krahe, T.E., Govindaiah, G. & Guido, W. (2015). Retinal and tectal “driver-like” inputs converge in the shell of the mouse dorsal lateral geniculate nucleus. Journal of Neuroscience 35, 10523–10534.CrossRefGoogle ScholarPubMed
Bleckert, A., Schwartz, G.W., Turner, M.H., Rieke, F. & Wong, R.O. (2014). Visual space is represented by nonmatching topographies of distinct mouse retinal ganglion cell types. Current Biology 24, 310–315.Google Scholar
Borst, A. & Euler, T. (2011). Seeing things in motion: Models, circuits, and mechanisms. Neuron 71, 974–994.Google Scholar
Brown, T.M., Gias, C., Hatori, M., Keding, S.R., Semo, M., Coffey, P.J., Gigg, J., Piggins, H.D., Panda, S. & Lucas, R.J. (2010). Melanopsin contributions to irradiance coding in the thalamo-cortical visual system. PLoS Biology 8, e1000558.CrossRefGoogle ScholarPubMed
Burbridge, T.J., Xu, H.P., Ackman, J.B., Ge, X., Zhang, Y., Ye, M.J., Zhou, Z.J., Xu, J., Contractor, A. & Crair, M.C. (2014). Visual circuit development requires patterned activity mediated by retinal acetylcholine receptors. Neuron 84, 1049–1064.CrossRefGoogle ScholarPubMed
Cang, J. & Feldheim, D.A. (2013). Developmental mechanisms of topographic map formation and alignment. Annual Review of Neuroscience 36, 51–77.Google Scholar
Cang, J., Niell, C.M., Liu, X., Pfeiffenberger, C., Feldheim, D.A. & Stryker, M.P. (2008). Selective disruption of one Cartesian axis of cortical maps and receptive fields by deficiency in ephrin-As and structured activity. Neuron 57, 511–523.Google Scholar
Chapman, B. (2000). Necessity for afferent activity to maintain eye-specific segregation in ferret lateral geniculate nucleus. Science 287, 2479–2482.Google Scholar
Chen, C., Bickford, M.E. & Hirsch, J.A. (2016). Untangling the web between eye and brain. Cell 165, 20–21.CrossRefGoogle ScholarPubMed
Chen, C. & Regehr, W.G. (2000). Developmental remodeling of the retinogeniculate synapse. Neuron 28, 955–966.CrossRefGoogle ScholarPubMed
Coleman, J.E., Law, K. & Bear, M.F. (2009). Anatomical origins of ocular dominance in mouse primary visual cortex. Neuroscience 161, 561–571.Google Scholar
Coombs, J., van der List, D., Wang, G.Y. & Chalupa, L.M. (2006). Morphological properties of mouse retinal ganglion cells. Neuroscience 140, 123–136.CrossRefGoogle ScholarPubMed
Cruz-Martin, A., El-Danaf, R.N., Osakada, F., Sriram, B., Dhande, O.S., Nguyen, P.L., Callaway, E.M., Ghosh, A. & Huberman, A.D. (2014). A dedicated circuit links direction-selective retinal ganglion cells to the primary visual cortex. Nature 507, 358–361.CrossRefGoogle ScholarPubMed
Dacey, D.M., Peterson, B.B., Robinson, F.R. & Gamlin, P.D. (2003). Fireworks in the primate retina: In vitro photodynamics reveals diverse LGN-projecting ganglion cell types. Neuron 37, 15–27.Google Scholar
de Monasterio, F.M. (1978). Properties of ganglion cells with atypical receptive-field organization in retina of macaques. Journal of Neurophysiology 41, 1435–1449.Google Scholar
Demas, J., Sagdullaev, B.T., Green, E., Jaubert-Miazza, L., McCall, M.A., Gregg, R.G., Wong, R.O. & Guido, W. (2006). Failure to maintain eye-specific segregation in nob, a mutant with abnormally patterned retinal activity. Neuron 50, 247–259.Google Scholar
Demeulemeester, H., Arckens, L., Vandesande, F., Orban, G.A., Heizmann, C.W. & Pochet, R. (1991). Calcium binding proteins as molecular markers for cat geniculate neurons. Experimental Brain Research 83, 513–520.Google Scholar
Denman, D.J. & Contreras, D. (2016). On parallel streams through the mouse dorsal lateral geniculate nucleus. Frontiers in Neural Circuits 10, 20.Google Scholar
Dhande, O.S., Bhatt, S., Anishchenko, A., Elstrott, J., Iwasato, T., Swindell, E.C., Xu, H.P., Jamrich, M., Itohara, S., Feller, M.B. & Crair, M.C. (2012). Role of adenylate cyclase 1 in retinofugal map development. Journal of Comparative Neurology 520, 1562–1583.CrossRefGoogle ScholarPubMed
Dhande, O.S., Estevez, M.E., Quattrochi, L.E., El-Danaf, R.N., Nguyen, P.L., Berson, D.M. & Huberman, A.D. (2013). Genetic dissection of retinal inputs to brainstem nuclei controlling image stabilization. Journal of Neuroscience 33, 17797–17813.Google Scholar
Dhande, O.S., Hua, E.W., Guh, E., Yeh, J., Bhatt, S., Zhang, Y., Ruthazer, E.S., Feller, M.B. & Crair, M.C. (2011). Development of single retinofugal axon arbors in normal and beta2 knock-out mice. Journal of Neuroscience 31, 3384–3399.Google Scholar
Dhande, O.S. & Huberman, A.D. (2014). Retinal ganglion cell maps in the brain: Implications for visual processing. Current Opinion in Neurobiology 24, 133–142.Google Scholar
Dhande, O.S., Stafford, B.K., Lim, J-H.A. & Huberman, A.D. (2015). Contributions of retinal ganglion cells to subcortical visual processing and behaviors. Annual Review of Vision Science 1, 291–328.Google Scholar
Duan, X., Krishnaswamy, A., De la Huerta, I. & Sanes, J.R. (2014). Type II cadherins guide assembly of a direction-selective retinal circuit. Cell 158, 793–807.Google Scholar
Durand, S., Iyer, R., Mizuseki, K., de Vries, S., Mihalas, S. & Reid, R.C. (2016). A comparison of visual response properties in the lateral geniculate nucleus and primary visual cortex of awake and anesthetized mice. Journal of Neuroscience 36, 12144–12156.Google Scholar
Ecker, J.L., Dumitrescu, O.N., Wong, K.Y., Alam, N.M., Chen, S.K., LeGates, T., Renna, J.M., Prusky, G.T., Berson, D.M. & Hattar, S. (2010). Melanopsin-expressing retinal ganglion-cell photoreceptors: Cellular diversity and role in pattern vision. Neuron 67, 49–60.Google Scholar
El-Danaf, R.N., Krahe, T.E., Dilger, E.K., Bickford, M.E., Fox, M.A. & Guido, W. (2015). Developmental remodeling of relay cells in the dorsal lateral geniculate nucleus in the absence of retinal input. Neural Development 10, 19.CrossRefGoogle ScholarPubMed
Ellis, E.M., Gauvain, G., Sivyer, B. & Murphy, G.J. (2016). Shared and distinct retinal input to the mouse superior colliculus and dorsal lateral geniculate nucleus. Journal of Neurophysiology 116, 602–610.Google Scholar
Estevez, M.E., Fogerson, P.M., Ilardi, M.C., Borghuis, B.G., Chan, E., Weng, S., Auferkorte, O.N., Demb, J.B. & Berson, D.M. (2012). Form and function of the M4 cell, an intrinsically photosensitive retinal ganglion cell type contributing to geniculocortical vision. Journal of Neuroscience 32, 13608–13620.Google Scholar
Farrow, K., Teixeira, M., Szikra, T., Viney, T.J., Balint, K., Yonehara, K. & Roska, B. (2013). Ambient illumination toggles a neuronal circuit switch in the retina and visual perception at cone threshold. Neuron 78, 325–338.Google Scholar
Field, G.D. & Chichilnisky, E.J. (2007). Information processing in the primate retina: Circuitry and coding. Annual Review of Neuroscience 30, 1–30.Google Scholar
Friedlander, M.J., Lin, C.S., Stanford, L.R. & Sherman, S.M. (1981). Morphology of functionally identified neurons in lateral geniculate nucleus of the cat. Journal of Neurophysiology 46, 80–129.Google Scholar
Gauvain, G. & Murphy, G.J. (2015). Projection-specific characteristics of retinal input to the brain. Journal of Neuroscience 35, 6575–6583.Google Scholar
Godement, P., Salaun, J. & Imbert, M. (1984). Prenatal and postnatal development of retinogeniculate and retinocollicular projections in the mouse. Journal of Comparative Neurology 230, 552–575.CrossRefGoogle ScholarPubMed
Grieve, K.L. (2005). Binocular visual responses in cells of the rat dLGN. The Journal of Physiology 566, 119–124.CrossRefGoogle ScholarPubMed
Grubb, M.S., Rossi, F.M., Changeux, J.P. & Thompson, I.D. (2003). Abnormal functional organization in the dorsal lateral geniculate nucleus of mice lacking the beta 2 subunit of the nicotinic acetylcholine receptor. Neuron 40, 1161–1172.CrossRefGoogle ScholarPubMed
Grubb, M.S. & Thompson, I.D. (2003). Quantitative characterization of visual response properties in the mouse dorsal lateral geniculate nucleus. Journal of Neurophysiology 90, 3594–3607.CrossRefGoogle ScholarPubMed
Grubb, M.S. & Thompson, I.D. (2004). Biochemical and anatomical subdivision of the dorsal lateral geniculate nucleus in normal mice and in mice lacking the beta2 subunit of the nicotinic acetylcholine receptor. Vision Research 44, 3365–3376.Google Scholar
Guido, W. (2008). Refinement of the retinogeniculate pathway. The Journal of Physiology 586, 4357–4362.Google Scholar
Guido, W., Tumosa, N. & Spear, P.D. (1989). Binocular interactions in the cat’s dorsal lateral geniculate nucleus. I. Spatial-frequency analysis of responses of X, Y, and W cells to nondominant-eye stimulation. Journal of Neurophysiology 62, 526–543.Google Scholar
Hammer, S., Monavarfeshani, A., Lemon, T., Su, J. & Fox, M.A. (2015). Multiple retinal axons converge onto relay cells in the adult mouse thalamus. Cell Reports 12, 1575–1583.Google Scholar
Hamos, J.E., Van Horn, S.C., Raczkowski, D. & Sherman, S.M. (1987). Synaptic circuits involving an individual retinogeniculate axon in the cat. Journal of Comparative Neurology 259, 165–192.Google Scholar
Harting, J.K., Huerta, M.F., Hashikawa, T. & van Lieshout, D.P. (1991). Projection of the mammalian superior colliculus upon the dorsal lateral geniculate nucleus: Organization of tectogeniculate pathways in nineteen species. Journal of Comparative Neurology 304, 275–306.Google Scholar
Hattar, S., Kumar, M., Park, A., Tong, P., Tung, J., Yau, K.W. & Berson, D.M. (2006). Central projections of melanopsin-expressing retinal ganglion cells in the mouse. Journal of Comparative Neurology 497, 326–349.Google Scholar
Hattar, S., Liao, H.W., Takao, M., Berson, D.M. & Yau, K.W. (2002). Melanopsin-containing retinal ganglion cells: Architecture, projections, and intrinsic photosensitivity. Science 295, 1065–1070.CrossRefGoogle ScholarPubMed
Helmstaedter, M., Briggman, K.L., Turaga, S.C., Jain, V., Seung, H.S. & Denk, W. (2013). Connectomic reconstruction of the inner plexiform layer in the mouse retina. Nature 500, 168–174.CrossRefGoogle ScholarPubMed
Hong, Y.K. & Chen, C. (2011). Wiring and rewiring of the retinogeniculate synapse. Current Opinion in Neurobiology 21, 228–237.Google Scholar
Hong, Y.K., Park, S., Litvina, E.Y., Morales, J., Sanes, J.R. & Chen, C. (2014). Refinement of the retinogeniculate synapse by bouton clustering. Neuron 84, 332–339.Google Scholar
Howarth, M., Walmsley, L. & Brown, T.M. (2014). Binocular integration in the mouse lateral geniculate nuclei. Current Biology 24, 1241–1247.Google Scholar
Hubel, D.H. & Wiesel, T.N. (1961). Integrative action in the cat’s lateral geniculate body. The Journal of Physiology 155, 385–398.CrossRefGoogle ScholarPubMed
Huberman, A.D., Manu, M., Koch, S.M., Susman, M.W., Lutz, A.B., Ullian, E.M., Baccus, S.A. & Barres, B.A. (2008). Architecture and activity-mediated refinement of axonal projections from a mosaic of genetically identified retinal ganglion cells. Neuron 59, 425–438.Google Scholar
Huberman, A.D., Murray, K.D., Warland, D.K., Feldheim, D.A. & Chapman, B. (2005). Ephrin-As mediate targeting of eye-specific projections to the lateral geniculate nucleus. Nature Neuroscience 8, 1013–1021.Google Scholar
Huberman, A.D., Wei, W., Elstrott, J., Stafford, B.K., Feller, M.B. & Barres, B.A. (2009). Genetic identification of an ON–OFF direction-selective retinal ganglion cell subtype reveals a layer-specific subcortical map of posterior motion. Neuron 62, 327–334.Google Scholar
Ivanova, E., Lee, P. & Pan, Z.H. (2013). Characterization of multiple bistratified retinal ganglion cells in a purkinje cell protein 2-Cre transgenic mouse line. Journal of Comparative Neurology 521, 2165–2180.CrossRefGoogle Scholar
Jacoby, J., Zhu, Y., DeVries, S.H. & Schwartz, G.W. (2015). An amacrine cell circuit for signaling steady illumination in the retina. Cell Reports 13, 2663–2670.Google Scholar
Jaubert-Miazza, L., Green, E., Lo, F.S., Bui, K., Mills, J. & Guido, W. (2005). Structural and functional composition of the developing retinogeniculate pathway in the mouse. Visual Neuroscience 22, 661–676.CrossRefGoogle ScholarPubMed
Joesch, M. & Meister, M. (2016). A neuronal circuit for colour vision based on rod-cone opponency. Nature 532, 236–239.Google Scholar
Kay, J.N., De la Huerta, I., Kim, I.J., Zhang, Y., Yamagata, M., Chu, M.W., Meister, M. & Sanes, J.R. (2011). Retinal ganglion cells with distinct directional preferences differ in molecular identity, structure, and central projections. Journal of Neuroscience 31, 7753–7762.Google Scholar
Kim, I.J., Zhang, Y., Meister, M. & Sanes, J.R. (2010). Laminar restriction of retinal ganglion cell dendrites and axons: Subtype-specific developmental patterns revealed with transgenic markers. Journal of Neuroscience 30, 1452–1462.Google Scholar
Kim, I.J., Zhang, Y., Yamagata, M., Meister, M. & Sanes, J.R. (2008). Molecular identification of a retinal cell type that responds to upward motion. Nature 452, 478–482.CrossRefGoogle ScholarPubMed
Koch, S.M., Dela Cruz, C.G., Hnasko, T.S., Edwards, R.H., Huberman, A.D. & Ullian, E.M. (2011). Pathway-specific genetic attenuation of glutamate release alters select features of competition-based visual circuit refinement. Neuron 71, 235–242.Google Scholar
Krahe, T.E., El-Danaf, R.N., Dilger, E.K., Henderson, S.C. & Guido, W. (2011). Morphologically distinct classes of relay cells exhibit regional preferences in the dorsal lateral geniculate nucleus of the mouse. Journal of Neuroscience 31, 17437–17448.Google Scholar
Lee, B.B., Virsu, V. & Creutzfeldt, O.D. (1983). Linear signal transmission from prepotentials to cells in the macaque lateral geniculate nucleus. Experimental Brain Research 52, 50–56.CrossRefGoogle ScholarPubMed
Lee, S., Zhang, Y., Chen, M. & Zhou, Z.J. (2016). Segregated glycine–glutamate Co-transmission from vGluT3 amacrine cells to contrast-suppressed and contrast-enhanced retinal circuits. Neuron 90, 27–34.Google Scholar
Leist, M., Datunashvilli, M., Kanyshkova, T., Zobeiri, M., Aissaoui, A., Cerina, M., Romanelli, M.N., Pape, H.C., & Budde, T. (2016). Two types of interneurons in the mouse lateral geniculate nucleus are characterized by different h-current density. Scientific Reports 6, 24904.Google Scholar
Levick, W.R. (1967). Receptive fields and trigger features of ganglion cells in the visual streak of the rabbits retina. The Journal of Physiology 188, 285–307.Google Scholar
Levick, W.R., Cleland, B.G. & Dubin, M.W. (1972). Lateral geniculate neurons of cat: Retinal inputs and physiology. Investigative Ophthalmology 11, 302–311.Google Scholar
Marrocco, R.T. & McClurkin, J.W. (1979). Binocular interaction in the lateral geniculate nucleus of the monkey. Brain Research 168, 633–637.Google Scholar
Marshel, J.H., Garrett, M.E., Nauhaus, I. & Callaway, E.M. (2011). Functional specialization of seven mouse visual cortical areas. Neuron 72, 1040–1054.CrossRefGoogle ScholarPubMed
Marshel, J.H., Kaye, A.P., Nauhaus, I. & Callaway, E.M. (2012). Anterior–posterior direction opponency in the superficial mouse lateral geniculate nucleus. Neuron 76, 713–720.Google Scholar
Martersteck, E.M., Hirokawa, K.E., Evarts, M., Bernard, A., Duan, X., Li, Y., Ng, L., Oh, S.W., Ouellette, B., Royall, J.J., Stoecklin, M., Wang, Q., Zeng, H., Sanes, J.R. & Harris, J.A. (2017). Diverse central projection patterns of retinal ganglion cells. Cell Reports 18, 2058–2072.Google Scholar
Martin, P.R. (1986). The projection of different retinal ganglion cell classes to the dorsal lateral geniculate nucleus in the hooded rat. Experimental Brain Research 62, 77–88.Google Scholar
McLaughlin, T. & O’Leary, D.D. (2005). Molecular gradients and development of retinotopic maps. Annual Review of Neuroscience 28, 327–355.Google Scholar
Meister, M., Wong, R.O., Baylor, D.A. & Shatz, C.J. (1991). Synchronous bursts of action potentials in ganglion cells of the developing mammalian retina. Science 252, 939–943.CrossRefGoogle ScholarPubMed
Morgan, J.L., Berger, D.R., Wetzel, A.W. & Lichtman, J.W. (2016). The fuzzy logic of network connectivity in mouse visual thalamus. Cell 165, 192–206.CrossRefGoogle ScholarPubMed
Muir-Robinson, G., Hwang, B.J. & Feller, M.B. (2002). Retinogeniculate axons undergo eye-specific segregation in the absence of eye-specific layers. Journal of Neuroscience 22, 5259–5264.CrossRefGoogle ScholarPubMed
Murphy, G.J. & Rieke, F. (2006). Network variability limits stimulus-evoked spike timing precision in retinal ganglion cells. Neuron 52, 511–524.Google Scholar
Niell, C.M. (2013). Vision: More than expected in the early visual system. Current Biology 23, R681–684.Google Scholar
Niell, C.M. & Stryker, M.P. (2010). Modulation of visual responses by behavioral state in mouse visual cortex. Neuron 65, 472–479.CrossRefGoogle Scholar
Osterhout, J.A., El-Danaf, R.N., Nguyen, P.L. & Huberman, A.D. (2014). Birthdate and outgrowth timing predict cellular mechanisms of axon target matching in the developing visual pathway. Cell Reports 8, 1006–1017.Google Scholar
Osterhout, J.A., Stafford, B.K., Nguyen, P.L., Yoshihara, Y. & Huberman, A.D. (2015). Contactin-4 mediates axon-target specificity and functional development of the accessory optic system. Neuron 86, 985–999.Google Scholar
Pang, J.J., Gao, F. & Wu, S.M. (2003). Light-evoked excitatory and inhibitory synaptic inputs to ON and OFF alpha ganglion cells in the mouse retina. Journal of Neuroscience 23, 6063–6073.Google Scholar
Park, S.J., Borghuis, B.G., Rahmani, P., Zeng, Q., Kim, I.J. & Demb, J.B. (2015). Function and circuitry of VIP+ interneurons in the mouse retina. Journal of Neuroscience 35, 10685–10700.Google Scholar
Parnavelas, J.G., Mounty, E.J., Bradford, R. & Lieberman, A.R. (1977). The postnatal development of neurons in the dorsal lateral geniculate nucleus of the rat: A Golgi study. Journal of Comparative Neurology 171, 481–499.Google Scholar
Petros, T.J., Rebsam, A. & Mason, C.A. (2008). Retinal axon growth at the optic chiasm: To cross or not to cross. Annual Review of Neuroscience 31, 295–315.CrossRefGoogle ScholarPubMed
Pfeiffenberger, C., Cutforth, T., Woods, G., Yamada, J., Renteria, R.C., Copenhagen, D.R., Flanagan, J.G. & Feldheim, D.A. (2005). Ephrin-As and neural activity are required for eye-specific patterning during retinogeniculate mapping. Nature Neuroscience 8, 1022–1027.Google Scholar
Pfeiffenberger, C., Yamada, J. & Feldheim, D.A. (2006). Ephrin-As and patterned retinal activity act together in the development of topographic maps in the primary visual system. Journal of Neuroscience 26, 12873–12884.Google Scholar
Pinault, D. (2004). The thalamic reticular nucleus: Structure, function and concept. Brain Research Reviews 46, 1–31.CrossRefGoogle ScholarPubMed
Piscopo, D.M., El-Danaf, R.N., Huberman, A.D. & Niell, C.M. (2013). Diverse visual features encoded in mouse lateral geniculate nucleus. Journal of Neuroscience 33, 4642–4656.CrossRefGoogle ScholarPubMed
Prigge, C.L., Yeh, P.T., Liou, N.F., Lee, C.C., You, S.F., Liu, L.L., McNeill, D.S., Chew, K.S., Hattar, S., Chen, S.K. & Zhang, D.Q. (2016). M1 ipRGCs influence visual function through retrograde signaling in the retina. Journal of Neuroscience 36, 7184–7197.Google Scholar
Provencio, I., Rodriguez, I.R., Jiang, G., Hayes, W.P., Moreira, E.F. & Rollag, M.D. (2000). A novel human opsin in the inner retina. Journal of Neuroscience 20, 600–605.Google Scholar
Rafols, J.A. & Valverde, F. (1973). The structure of the dorsal lateral geniculate nucleus in the mouse. A Golgi and electron microscopic study. Journal of Comparative Neurology 150, 303–332.Google Scholar
Reese, B.E. (1988). ‘Hidden lamination’ in the dorsal lateral geniculate nucleus: The functional organization of this thalamic region in the rat. Brain Research 472, 119–137.Google Scholar
Reese, B.E. & Jeffery, G. (1983). Crossed and uncrossed visual topography in dorsal lateral geniculate nucleus of the pigmented rat. Journal of Neurophysiology 49, 877–885.CrossRefGoogle ScholarPubMed
Reifler, A.N., Chervenak, A.P., Dolikian, M.E., Benenati, B.A., Li, B.Y., Wachter, R.D., Lynch, A.M., Demertzis, Z.D., Meyers, B.S., Abufarha, F.S., Jaeckel, E.R., Flannery, M.P. & Wong, K.Y. (2015). All spiking, sustained ON displaced amacrine cells receive gap-junction input from melanopsin ganglion cells. Current Biology 25, 2763–2773.CrossRefGoogle ScholarPubMed
Rivlin-Etzion, M., Zhou, K., Wei, W., Elstrott, J., Nguyen, P.L., Barres, B.A., Huberman, A.D. & Feller, M.B. (2011). Transgenic mice reveal unexpected diversity of on–off direction-selective retinal ganglion cell subtypes and brain structures involved in motion processing. Journal of Neuroscience 31, 8760–8769.CrossRefGoogle ScholarPubMed
Rodieck, R.W. (1967). Receptive fields in the cat retina: A new type. Science 157, 90–92.Google Scholar
Rompani, S.B., Mullner, F.E., Wanner, A., Zhang, C., Roth, C.N., Yonehara, K. & Roska, B. (2017). Different modes of visual integration in the lateral geniculate nucleus revealed by single-cell-initiated transsynaptic tracing. Neuron 93, 767–776.Google Scholar
Roth, M.M., Helmchen, F. & Kampa, B.M. (2012). Distinct functional properties of primary and posteromedial visual area of mouse neocortex. Journal of Neuroscience 32, 9716–9726.CrossRefGoogle ScholarPubMed
Rousso, D.L., Qiao, M., Kagan, R.D., Yamagata, M., Palmiter, R.D. & Sanes, J.R. (2016). Two pairs of ON and OFF retinal ganglion cells are defined by intersectional patterns of transcription factor expression. Cell Reports 15, 1930–1944.Google Scholar
Sanes, J.R. & Masland, R.H. (2015). The types of retinal ganglion cells: Current status and implications for neuronal classification. Annual Review of Neuroscience 38, 221–246.Google Scholar
Schmidt, T.M., Alam, N.M., Chen, S., Kofuji, P., Li, W., Prusky, G.T. & Hattar, S. (2014). A role for melanopsin in alpha retinal ganglion cells and contrast detection. Neuron 82, 781–788.Google Scholar
Schmidt, T.M., Chen, S.K. & Hattar, S. (2011). Intrinsically photosensitive retinal ganglion cells: Many subtypes, diverse functions. Trends in Neurosciences 34, 572–580.Google Scholar
Schmidt, T.M. & Kofuji, P. (2009). Functional and morphological differences among intrinsically photosensitive retinal ganglion cells. Journal of Neuroscience 29, 476–482.Google Scholar
Scholl, B., Tan, A.Y., Corey, J. & Priebe, N.J. (2013). Emergence of orientation selectivity in the mammalian visual pathway. Journal of Neuroscience 33, 10616–10624.Google Scholar
Seabrook, T.A., Krahe, T.E., Govindaiah, G. & Guido, W. (2013). Interneurons in the mouse visual thalamus maintain a high degree of retinal convergence throughout postnatal development. Neural Development 8, 24.Google Scholar
Sherman, S.M. (2004). Interneurons and triadic circuitry of the thalamus. Trends in Neurosciences 27, 670–675.Google Scholar
Sherman, S.M. & Guillery, R.W. (2002). The role of the thalamus in the flow of information to the cortex. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences 357, 1695–1708.Google Scholar
Siegert, S., Scherf, B.G., Del Punta, K., Didkovsky, N., Heintz, N. & Roska, B. (2009). Genetic address book for retinal cell types. Nature Neuroscience 12, 1197–1204.Google Scholar
Simpson, J.I. (1984). The accessory optic system. Annual Review of Neuroscience 7, 13–41.Google Scholar
Sivyer, B., Taylor, W.R. & Vaney, D.I. (2010). Uniformity detector retinal ganglion cells fire complex spikes and receive only light-evoked inhibition. Proceedings of the National Academy of Sciences of the United States of America 107, 5628–5633.Google Scholar
Soto, F., Ma, X., Cecil, J.L., Vo, B.Q., Culican, S.M. & Kerschensteiner, D. (2012). Spontaneous activity promotes synapse formation in a cell-type-dependent manner in the developing retina. Journal of Neuroscience 32, 5426–5439.Google Scholar
Stanford, L.R., Friedlander, M.J. & Sherman, S.M. (1981). Morphology of physiologically identified W-cells in the C laminae of the cat’s lateral geniculate nucleus. Journal of Neuroscience 1, 578–584.Google Scholar
Stanford, L.R., Friedlander, M.J. & Sherman, S.M. (1983). Morphological and physiological properties of geniculate W-cells of the cat: A comparison with X- and Y-cells. Journal of Neurophysiology 50, 582–608.Google Scholar
Stellwagen, D. & Shatz, C.J. (2002). An instructive role for retinal waves in the development of retinogeniculate connectivity. Neuron 33, 357–367.Google Scholar
Sumbul, U., Song, S., McCulloch, K., Becker, M., Lin, B., Sanes, J.R., Masland, R.H. & Seung, H.S. (2014). A genetic and computational approach to structurally classify neuronal types. Nature Communications 5, 3512.Google Scholar
Sun, L.O., Brady, C.M., Cahill, H., Al-Khindi, T., Sakuta, H., Dhande, O.S., Noda, M., Huberman, A.D., Nathans, J. & Kolodkin, A.L. (2015). Functional assembly of accessory optic system circuitry critical for compensatory eye movements. Neuron 86, 971–984.CrossRefGoogle ScholarPubMed
Sun, W., Li, N. & He, S. (2002). Large-scale morphological survey of mouse retinal ganglion cells. Journal of Comparative Neurology 451, 115–126.Google Scholar
Suresh, V., Ciftcioglu, U.M., Wang, X., Lala, B.M., Ding, K.R., Smith, W.A., Sommer, F.T. & Hirsch, J.A. (2016). Synaptic contributions to receptive field structure and response properties in the rodent lateral geniculate nucleus of the thalamus. Journal of Neuroscience 36, 10949–10963.Google Scholar
Tang, J., Ardila Jimenez, S.C., Chakraborty, S. & Schultz, S.R. (2016). Visual receptive field properties of neurons in the mouse lateral geniculate nucleus. PLoS One 11, e0146017.Google Scholar
Tavazoie, S.F. & Reid, R.C. (2000). Diverse receptive fields in the lateral geniculate nucleus during thalamocortical development. Nature Neuroscience 3, 608–616.Google Scholar
Tien, N.W., Kim, T. & Kerschensteiner, D. (2016). Target-specific glycinergic transmission from VGluT3-expressing amacrine cells shapes suppressive contrast responses in the retina. Cell Reports 15, 1369–1375.Google Scholar
Tien, N.W., Pearson, J.T., Heller, C.R., Demas, J. & Kerschensteiner, D. (2015). Genetically identified suppressed-by-contrast retinal ganglion cells reliably signal self-generated visual stimuli. Journal of Neuroscience 35, 10815–10820.Google Scholar
Tu, D.C., Zhang, D., Demas, J., Slutsky, E.B., Provencio, I., Holy, T.E. & Van Gelder, R.N. (2005). Physiologic diversity and development of intrinsically photosensitive retinal ganglion cells. Neuron 48, 987–999.Google Scholar
Usrey, W.M. & Alitto, H.J. (2015). Visual functions of the thalamus. Annual Review of Vision Science 1, 351–371.Google Scholar
Wang, Q., Gao, E. & Burkhalter, A. (2011). Gateways of ventral and dorsal streams in mouse visual cortex. Journal of Neuroscience 31, 1905–1918.CrossRefGoogle ScholarPubMed
Wang, Q., Sporns, O. & Burkhalter, A. (2012). Network analysis of corticocortical connections reveals ventral and dorsal processing streams in mouse visual cortex. Journal of Neuroscience 32, 4386–4399.Google Scholar
Wong, K.Y., Dunn, F.A., Graham, D.M. & Berson, D.M. (2007). Synaptic influences on rat ganglion-cell photoreceptors. The Journal of Physiology 582, 279–296.Google Scholar
Xu, H.P., Burbridge, T.J., Chen, M.G., Ge, X., Zhang, Y., Zhou, Z.J. & Crair, M.C. (2015). Spatial pattern of spontaneous retinal waves instructs retinotopic map refinement more than activity frequency. Developmental Neurobiology 75, 621–640.Google Scholar
Yonehara, K., Ishikane, H., Sakuta, H., Shintani, T., Nakamura-Yonehara, K., Kamiji, N.L., Usui, S. & Noda, M. (2009). Identification of retinal ganglion cells and their projections involved in central transmission of information about upward and downward image motion. PLoS One 4, e4320.Google Scholar
Zhang, D.Q., Wong, K.Y., Sollars, P.J., Berson, D.M., Pickard, G.E. & McMahon, D.G. (2008). Intraretinal signaling by ganglion cell photoreceptors to dopaminergic amacrine neurons. Proceedings of the National Academy of Sciences of the United States of America 105, 14181–14186.Google Scholar
Zhang, J., Ackman, J.B., Xu, H.P. & Crair, M.C. (2011). Visual map development depends on the temporal pattern of binocular activity in mice. Nature Neuroscience 15, 298–307.Google Scholar
Zhao, X., Chen, H., Liu, X. & Cang, J. (2013a). Orientation-selective responses in the mouse lateral geniculate nucleus. Journal of Neuroscience 33, 12751–12763.Google Scholar
Zhao, X., Liu, M. & Cang, J. (2013b). Sublinear binocular integration preserves orientation selectivity in mouse visual cortex. Nature Communications 4, 2088.Google Scholar
Zhu, Y., Xu, J., Hauswirth, W.W. & DeVries, S.H. (2014). Genetically targeted binary labeling of retinal neurons. Journal of Neuroscience 34, 7845–7861.Google Scholar
Ziburkus, J. & Guido, W. (2006). Loss of binocular responses and reduced retinal convergence during the period of retinogeniculate axon segregation. Journal of Neurophysiology 96, 2775–2784.Google Scholar
Figure 0

Fig. 1. Schematics illustrate the organization of mouse dLGN. (A) Pattern of projections for different RGC cell types. (B) Hidden lamination in mouse dLGN. Left: Eye specific patterning of retinal projections arising from the contralateral (green) and ipsilateral eye. Right: Shell (blue) and core (purple) subdivisions. The shell receives convergent input from DSGCs and the superficial layers of the superior colliculus. The core receives input largely from RGCs with a canonical center surround organization. (C) Dendritic architecture of different classes of relay neurons (X, Y, W) and interneurons along with their regional preferences within dLGN.

Figure 1

Fig. 2. Circuit diagram that depicts retinal (red) and nonretinal (blue) connections of intrinsic interneurons and thalamocortical relay neurons of mouse dLGN.