Recent research has established that the superior colliculus (SC) plays a key role in visual motion processing and visually guided behaviors. However, differences across species have made it difficult to integrate findings from various animal models to form a general understanding of the SC. Here we use the tree shrew - a species evolutionarily intermediate between rodents and primates - to help bridge our understanding of this ancient brain structure. We recorded visual responses from the tree shrew (of either sex) SC neurons in vivo using a battery of motion stimuli, including drifting gratings, random dot kinematograms, and plaid patterns of superimposed gratings. Tree shrew SC neurons overall preferred low spatial and high temporal frequencies, as well as high speed of motion. They showed a mixed selectivity for motion components and integrated pattern, with integration consistent with a vector sum rule. Compared to mice, tree shrew SC showed similar tuning properties to basic visual features but exhibited a lower degree of motion integration reminiscent of visual cortices in other species. Finally, tree shrews displayed optokinetic eye movements, a visual-motion-induced reflexive behavior, and the response induced by plaids largely followed the vector sum rule. Together, our study provides fundamental insights into visual motion representation in the tree shrew SC and establishes a foundation for future comparative studies on visual processing in the SC.

Significance statement The tree shrew is an emerging model in visual neuroscience, offering a bridge between rodent and primate systems. Here, we systematically characterize how neurons in the tree shrew superior colliculus, a critical brain structure in visual processing, encodes and integrates visual motion. Our results reveal a mixture of conserved, intermediate, and species-specific features of motion processing, filling the gap of previously divergent observations across species. These findings demonstrate that the tree shrew is a useful model for studying neural basis of vision and provide insights into the evolution and implementation of motion computation in the brain.

Sensory stimuli are encoded by the neuronal firing patterns they evoke in the brain. This neural code becomes less correlated as information ascends through the visual system. In the primary visual cortex (V1), a spatial frequency (SF) tuning shift from coarse to fine features occurs alongside a reduction in correlations between stimulus representations. Our previous study suggested that this decorrelation is facilitated by coarse-to-fine processing in V1. However, there is evidence that coarse-to-fine processing emerges in the upstream dorsal lateral geniculate nucleus (dLGN), and it is unknown whether correlations between stimulus representations also decrease in this brain region. Therefore, the extent to which decorrelation is inherited from dLGN, is driven by local circuit dynamics in V1, or is the result of synergy between these areas is unknown. In this study, we compared extracellular neuronal activity recorded from dLGN and V1 of mice (of either sex) in response to sinusoidal gratings of different SFs. Despite also exhibiting coarse-to-fine processing, dLGN did not exhibit decorrelation in contrast to V1, suggesting that decorrelation emerges following a cortical transformation. In V1, many units exhibited a delayed shift to suppression that interacted with coarse-to-fine shifts on a time course coinciding with the decorrelation. Our results are therefore consistent with decorrelation emerging in V1 from a synergy between response properties in both dLGN and V1. These results demonstrate that geniculocortical dynamics enable discrimination between rich visual details and highlight the importance of cross-regional synergy to sensory processing.

The superior colliculus (SC), a midbrain sensorimotor hub, is anatomically and functionally similar across vertebrates, but how its cell types have evolved is unclear. Using single-nucleus transcriptomics, we compared the SC’s molecular and cellular organization in mice, tree shrews, and humans. Despite over 96 million years of evolutionary divergence, we identified ~30 consensus neuronal subtypes, including Cbln2+ neurons that form the SC-pulvinar circuit in mice and tree shrews. Synapse-related genes were among the most conserved in the SC, unlike neocortex, suggesting co-conservation of synaptic genes and collicular circuitry. In contrast, cilia-related genes diverged significantly across species, highlighting the potential importance of the neuronal primary cilium in SC evolution. Additionally, we identified an inhibitory SC neuron in tree shrews and humans but not mice. Our findings reveal that the SC has evolved by conserving neuron subtypes, synaptic genes, and circuitry, while diversifying ciliary gene expression and an inhibitory neuron subtype.

Recent studies have revealed diverse neuron types in the superior colliculus (SC), a midbrain structure critical for sensorimotor transformation. Here, as an important step toward studying the function of these subtypes, we characterize 10 transgenic mouse lines based on a recently published molecular atlas of the superficial SC. We show that Cre or fluorescence expression in some lines corresponds specifically to certain transcriptomic neuron types. These include two GENSAT lines that have been used to target morphological cell types in the SC and three knockin lines. In contrast, such a correspondence is not seen in other tested mice. Importantly, the expression pattern of marker genes in all these lines is highly consistent with the molecular atlas. Together, our studies support a correlation between morphological and transcriptomic neuron types, identify useful lines for targeting SC neuron types genetically, and demonstrate the validity of the single-cell transcriptomics data.

Visual motion is a crucial cue for the brain to track objects and take appropriate actions, enabling effective interactions with the environment. Here, we study how the superior colliculus (SC) integrates motion information using asymmetric plaids composed of drifting gratings of different directions and speeds. With both in vivo electrophysiology and two-photon calcium imaging, we find that mouse SC neurons integrate motion direction by performing vector summation of the component gratings. The computation is constrained probabilistically by the possible physical motions consistent with each grating. Excitatory and inhibitory SC neurons respond similarly to the plaid stimuli. Finally, the probabilistically constrained vector summation also guides optokinetic eye movements. Such a computation is fundamentally different from that in the visual cortex, where motion integration follows the intersection of the constraints. Our studies thus demonstrate a novel neural computation in motion processing and raise intriguing questions regarding its neuronal implementation and functional significance.

The superior colliculus (SC) is a conserved midbrain structure that is important for transforming visual and other sensory information into motor actions. Decades of investigations in numerous species have made the SC and its nonmammalian homologue, the optic tectum, one of the best studied structures in the brain, with rich information now available regarding its anatomical organization, its extensive inputs and outputs and its important functions in many reflexive and cognitive behaviours. Excitingly, recent studies using modern genomic and physiological approaches have begun to reveal the diverse neuronal subtypes in the SC, as well as their unique functions in visuomotor transformation. Studies have also started to uncover how subtypes of SC neurons form intricate circuits to mediate visual processing and visually guided behaviours. Here, we review these recent discoveries on the cell types and neuronal circuits underlying visuomotor transformations mediated by the SC. We also highlight the important future directions made possible by these new developments.

The superior colliculus (SC) is a prominent and conserved visual center in all vertebrates. In mice, the most superficial lamina of the SC is enriched with neurons that are selective for the moving direction of visual stimuli. Here we study how these direction selective neurons respond to complex motion patterns known as plaids, using two-photon calcium imaging in awake male and female mice. The plaid pattern consists of two superimposed sinusoidal gratings moving in different directions, giving an apparent pattern direction that lies between the directions of the two component gratings. Most direction selective neurons in the mouse SC respond robustly to the plaids and show a high selectivity for the moving direction of the plaid pattern but not of its components. Pattern motion selectivity is seen in both excitatory and inhibitory SC neurons and is especially prevalent in response to plaids with large cross angles between the two component gratings. However, retinal inputs to the SC are ambiguous in their selectivity to pattern versus component motion. Modeling suggests that pattern motion selectivity in the SC can arise from a nonlinear transformation of converging retinal inputs. In contrast, the prevalence of pattern motion selective neurons is not seen in the primary visual cortex (V1). These results demonstrate an interesting difference between the SC and V1 in motion processing and reveal the SC as an important site for encoding pattern motion.

The brain combines 2-dimensional images received from the two eyes to form a percept of 3-dimensional surroundings. This process of binocular integration in the primary visual cortex (V1) serves as a useful model for studying how neural circuits generate emergent properties from multiple input signals. Here, we perform a thorough characterization of binocular integration using electrophysiological recordings in the V1 of awake adult male and female mice, by systematically varying the orientation and phase disparity of monocular and binocular stimuli. We reveal widespread binocular integration in mouse V1 and demonstrate that the three commonly studied binocular properties – ocular dominance, interocular matching, and disparity selectivity – are independent from each other. For individual neurons, the responses to monocular stimulation can predict the average amplitude of binocular response, but not its selectivity. Finally, the extensive and independent binocular integration of monocular inputs is seen across cortical layers, in both regular-spiking and fast-spiking neurons, regardless of stimulus design. Our data indicate that the current model of simple feedforward convergence is inadequate to account for binocular integration in mouse V1, thus suggesting an indispensable role played by intracortical circuits in binocular computation.

Significance Statement Binocular integration is an important step of visual processing that takes place in the visual cortex. Studying the process by which V1 neurons become selective for certain binocular disparities is informative about how neural circuits integrate multiple information streams at a more general level. Here, we systematically characterize binocular integration in mice. Our data demonstrate more widespread and complex binocular integration in mouse V1 than previously reported. Binocular responses cannot be explained by a simple convergence of monocular responses, contrary to the prevailing model of binocular integration. These findings thus indicate that intracortical circuits must be involved in the exquisite computation of binocular disparity, which would endow brain circuits with the plasticity needed for binocular development and processing.

The brain creates a single visual percept of the world with inputs from two eyes. This means that downstream structures must integrate information from the two eyes coherently. Not only does the brain meet this challenge effortlessly, it also uses small differences between the two eyes’ inputs, i.e., binocular disparity, to construct depth information in a perceptual process called stereopsis. Recent studies have advanced our understanding of the neural circuits underlying stereoscopic vision and its development. Here, we review these advances in the context of three binocular properties that have been most commonly studied for visual cortical neurons: ocular dominance of response magnitude, interocular matching of orientation preference, and response selectivity for binocular disparity. By focusing mostly on mouse studies, as well as recent studies using ferrets and tree shrews, we highlight unresolved controversies and significant knowledge gaps regarding the neural circuits underlying binocular vision. We note that in most ocular dominance studies, only monocular stimulations are used, which could lead to a mischaracterization of binocularity. On the other hand, much remains unknown regarding the circuit basis of interocular matching and disparity selectivity and its development. We conclude by outlining opportunities for future studies on the neural circuits and functional development of binocular integration in the early visual system.