Joint Encoding of Object Motion and Motion Direction in the Salamander Retina

The vertebrate retina: a window into the evolution of computation in the brain

Animal brains are probably the most complex computational machines on our planet, and like everything in biology, they are the product of evolution. Advances in developmental and palaeobiology have been expanding our general understanding of how nervous systems can change at a molecular and structural level. However, how these changes translate into altered function - that is, into 'computation' - remains comparatively sparsely explored. What, concretely, does it mean for neuronal computation when neurons change their morphology and connectivity, when new neurons appear or old ones disappear, or when transmitter systems are slowly modified over many generations? And how does evolution use these many possible knobs and dials to constantly tune computation to give rise to the amazing diversity in animal behaviours we see today? Addressing these major gaps of understanding benefits from choosing a suitable model system. Here, I present the vertebrate retina as one perhaps unusually promising candidate. The retina is ancient and displays highly conserved core organisational principles across the entire vertebrate lineage, alongside a myriad of adjustments across extant species that were shaped by the history of their visual ecology. Moreover, the computational logic of the retina is readily interrogated experimentally, and our existing understanding of retinal circuits in a handful of species can serve as an anchor when exploring the visual circuit adaptations across the entire vertebrate tree of life, from fish deep in the aphotic zone of the oceans to eagles soaring high up in the sky.

Transformation of Motion Pattern Selectivity from Retina to Superior Colliculus

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.

Learning low-dimensional generalizable natural features from retina using a U-net

Much of sensory neuroscience focuses on presenting stimuli that are chosen by the experimenter because they are parametric and easy to sample and are thought to be behaviorally relevant to the organism. However, it is not generally known what these relevant features are in complex, natural scenes. This work focuses on using the retinal encoding of natural movies to determine the presumably behaviorally-relevant features that the brain represents. It is prohibitive to parameterize a natural movie and its respective retinal encoding fully. We use time within a natural movie as a proxy for the whole suite of features evolving across the scene. We then use a task-agnostic deep architecture, an encoder-decoder, to model the retinal encoding process and characterize its representation of "time in the natural scene" in a compressed latent space. In our end-to-end training, an encoder learns a compressed latent representation from a large population of salamander retinal ganglion cells responding to natural movies, while a decoder samples from this compressed latent space to generate the appropriate future movie frame. By comparing latent representations of retinal activity from three movies, we find that the retina has a generalizable encoding for time in the natural scene: the precise, low-dimensional representation of time learned from one movie can be used to represent time in a different movie, with up to 17 ms resolution. We then show that static textures and velocity features of a natural movie are synergistic. The retina simultaneously encodes both to establishes a generalizable, low-dimensional representation of time in the natural scene.

A robust receptive field code for optic flow detection and decomposition during self-motion

The perception of optic flow is essential for any visually guided behavior of a moving animal. To mechanistically predict behavior and understand the emergence of self-motion perception in vertebrate brains, it is essential to systematically characterize the motion receptive fields (RFs) of optic-flow-processing neurons. Here, we present the fine-scale RFs of thousands of motion-sensitive neurons studied in the diencephalon and the midbrain of zebrafish. We found neurons that serve as linear filters and robustly encode directional and speed information of translation-induced optic flow. These neurons are topographically arranged in pretectum according to translation direction. The unambiguous encoding of translation enables the decomposition of translational and rotational self-motion information from mixed optic flow. In behavioral experiments, we successfully demonstrated the predicted decomposition in the optokinetic and optomotor responses. Together, our study reveals the algorithm and the neural implementation for self-motion estimation in a vertebrate visual system.

Linear and nonlinear chromatic integration in the mouse retina

The computations performed by a neural circuit depend on how it integrates its input signals into an output of its own. In the retina, ganglion cells integrate visual information over time, space, and chromatic channels. Unlike the former two, chromatic integration is largely unexplored. Analogous to classical studies of spatial integration, we here study chromatic integration in mouse retina by identifying chromatic stimuli for which activation from the green or UV color channel is maximally balanced by deactivation through the other color channel. This reveals nonlinear chromatic integration in subsets of On, Off, and On-Off ganglion cells. Unlike the latter two, nonlinear On cells display response suppression rather than activation under balanced chromatic stimulation. Furthermore, nonlinear chromatic integration occurs independently of nonlinear spatial integration, depends on contributions from the rod pathway and on surround inhibition, and may provide information about chromatic boundaries, such as the skyline in natural scenes.

Nonlinear Spatial Integration Underlies the Diversity of Retinal Ganglion Cell Responses to Natural Images

How neurons encode natural stimuli is a fundamental question for sensory neuroscience. In the early visual system, standard encoding models assume that neurons linearly filter incoming stimuli through their receptive fields, but artificial stimuli, such as contrast-reversing gratings, often reveal nonlinear spatial processing. We investigated to what extent such nonlinear processing is relevant for the encoding of natural images in retinal ganglion cells in mice of either sex.

How neurons encode natural stimuli is a fundamental question for sensory neuroscience. In the early visual system, standard encoding models assume that neurons linearly filter incoming stimuli through their receptive fields, but artificial stimuli, such as contrast-reversing gratings, often reveal nonlinear spatial processing. We investigated to what extent such nonlinear processing is relevant for the encoding of natural images in retinal ganglion cells in mice of either sex. We found that standard linear receptive field models yielded good predictions of responses to flashed natural images for a subset of cells but failed to capture the spiking activity for many others. Cells with poor model performance displayed pronounced sensitivity to fine spatial contrast and local signal rectification as the dominant nonlinearity. By contrast, sensitivity to high-frequency contrast-reversing gratings, a classical test for nonlinear spatial integration, was not a good predictor of model performance and thus did not capture the variability of nonlinear spatial integration under natural images. In addition, we also observed a class of nonlinear ganglion cells with inverse tuning for spatial contrast, responding more strongly to spatially homogeneous than to spatially structured stimuli. These findings highlight the diversity of receptive field nonlinearities as a crucial component for understanding early sensory encoding in the context of natural stimuli.

SIGNIFICANCE STATEMENT Experiments with artificial visual stimuli have revealed that many types of retinal ganglion cells pool spatial input signals nonlinearly. However, it is still unclear how relevant this nonlinear spatial integration is when the input signals are natural images. Here we analyze retinal responses to natural scenes in large populations of mouse ganglion cells. We show that nonlinear spatial integration strongly influences responses to natural images for some ganglion cells, but not for others. Cells with nonlinear spatial integration were sensitive to spatial structure inside their receptive fields, and a small group of cells displayed a surprising sensitivity to spatially homogeneous stimuli. Traditional analyses with contrast-reversing gratings did not predict this variability of nonlinear spatial integration under natural images.

What the salamander eye has been telling the vision scientist's brain

Salamanders have been habitual residents of research laboratories for more than a century, and their history in science is tightly interwoven with vision research. Nevertheless, many vision scientists - even those working with salamanders - may be unaware of how much our knowledge about vision, and particularly the retina, has been shaped by studying salamanders. In this review, we take a tour through the salamander history in vision science, highlighting the main contributions of salamanders to our understanding of the vertebrate retina. We further point out specificities of the salamander visual system and discuss the perspectives of this animal system for future vision research.

Global Motion Processing by Populations of Direction-Selective Retinal Ganglion Cells

Simple stimuli have been critical to understanding neural population codes in sensory systems. Yet it remains necessary to determine the extent to which this understanding generalizes to more complex conditions. To examine this problem, we measured how populations of direction-selective ganglion cells (DSGCs) from the retinas of male and female mice respond to a global motion stimulus with its direction and speed changing dynamically. We then examined the encoding and decoding of motion direction in both individual and populations of DSGCs. Individual cells integrated global motion over ∼200 ms, and responses were tuned to direction. However, responses were sparse and broadly tuned, which severely limited decoding performance from small DSGC populations. In contrast, larger populations compensated for response sparsity, enabling decoding with high temporal precision (<100 ms). At these timescales, correlated spiking was minimal and had little impact on decoding performance, unlike results obtained using simpler local motion stimuli decoded over longer timescales. We use these data to define different DSGC population decoding regimes that use or mitigate correlated spiking to achieve high-spatial versus high-temporal resolution.SIGNIFICANCE STATEMENT ON-OFF direction-selective ganglion cells (ooDSGCs) in the mammalian retina are typically thought to signal local motion to the brain. However, several recent studies suggest they may signal global motion. Here we analyze the fidelity of encoding and decoding global motion in a natural scene across large populations of ooDSGCs. We show that large populations of DSGCs are capable of signaling rapid changes in global motion.

Early Visual Motion Experience Improves Retinal Encoding of Motion Directions

Altered sensory experience in early life often leads to altered response properties of the sensory neurons. This process is mostly thought to happen in the brain, not in the sensory organs. We show that in the mouse retina of both sexes, exposed to a motion-dominated visual environment from eye-opening, the ON-OFF direction selective ganglion cells (ooDSGCs) develop significantly stronger direction encoding ability for motion in all directions. This improvement occurs independent of the motion direction used for training. We demonstrated that this enhanced ability to encode motion direction is mainly attributed to increased response reliability of ooDSGCs. Closer examination revealed that the excitatory inputs from the ON bipolar pathway showed enhanced response reliability after the motion experience training, while other synaptic inputs remain relatively unchanged. Our results demonstrate that retina adapts to the visual environment during neonatal development.SIGNIFICANCE STATEMENT We found that retina, as the first stage of visual sensation, can also be affected by experience dependent plasticity during development. Exposure to a motion enriched visual environment immediately after eye-opening greatly improves motion direction encoding by direction selective retinal ganglion cells (RGCs). These results motivate future studies aimed at understanding how visual experience shapes the retinal circuits and the response properties of retinal neurons.

Neural mechanisms of contextual modulation in the retinal direction selective circuit

Contextual modulation of neuronal responses by surrounding environments is a fundamental attribute of sensory processing. In the mammalian retina, responses of On–Off direction selective ganglion cells (DSGCs) are modulated by motion contexts. However, the underlying mechanisms are unknown. Here, we show that posterior-preferring DSGCs (pDSGCs) are sensitive to discontinuities of moving contours owing to contextually modulated cholinergic excitation from starburst amacrine cells (SACs). Using a combination of synapse-specific genetic manipulations, patch clamp electrophysiology and connectomic analysis, we identified distinct circuit motifs upstream of On and Off SACs that are required for the contextual modulation of pDSGC activity for bright and dark contrasts. Furthermore, our results reveal a class of wide-field amacrine cells (WACs) with straight, unbranching dendrites that function as “continuity detectors” of moving contours. Therefore, divergent circuit motifs in the On and Off pathways extend the information encoding of On-Off DSGCs beyond their direction selectivity during complex stimuli.

The mechanisms of contextual modulation in direction selective ganglion cells in the retina remain unclear. Here, the authors find that that On-Off direction-selective ganglion cells are differentially sensitive to discontinuities of dark and bright moving edges in the visual environment and, using synapse-specific genetic manipulations with functional measurements, reveal the microcircuits underlying this contextual sensitivity.

Activity Correlations between Direction-Selective Retinal Ganglion Cells Synergistically Enhance Motion Decoding from Complex Visual Scenes

Neurons in sensory systems are often tuned to particular stimulus features. During complex naturalistic stimulation, however, multiple features may simultaneously affect neuronal responses, which complicates the readout of individual features. To investigate feature representation under complex stimulation, we studied how direction-selective ganglion cells in salamander retina respond to texture motion where direction, velocity, and spatial pattern inside the receptive field continuously change. We found that the cells preserve their direction preference under this stimulation, yet their direction encoding becomes ambiguous due to simultaneous activation by luminance changes. The ambiguities can be resolved by considering populations of direction-selective cells with different preferred directions. This gives rise to synergistic motion decoding, yielding more information from the population than the summed information from single-cell responses. Strong positive response correlations between cells with different preferred directions amplify this synergy. Our results show how correlated population activity can enhance feature extraction in complex visual scenes.

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Direction-selective ganglion cells respond to motion as well as luminance changes

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This obscures the readout of direction from single cells under complex texture motion

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Population decoding improves direction readout supralinearly over individual cells

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Strong spike correlations further enhance readout through increased synergy

Inference of neuronal functional circuitry with spike-triggered non-negative matrix factorization

Neurons in sensory systems often pool inputs over arrays of presynaptic cells, giving rise to functional subunits inside a neuron’s receptive field. The organization of these subunits provides a signature of the neuron’s presynaptic functional connectivity and determines how the neuron integrates sensory stimuli. Here we introduce the method of spike-triggered non-negative matrix factorization for detecting the layout of subunits within a neuron’s receptive field. The method only requires the neuron’s spiking responses under finely structured sensory stimulation and is therefore applicable to large populations of simultaneously recorded neurons. Applied to recordings from ganglion cells in the salamander retina, the method retrieves the receptive fields of presynaptic bipolar cells, as verified by simultaneous bipolar and ganglion cell recordings. The identified subunit layouts allow improved predictions of ganglion cell responses to natural stimuli and reveal shared bipolar cell input into distinct types of ganglion cells.

How a neuron integrates sensory information requires knowledge about its functional presynaptic connections. Here the authors report a new method using non-negative matrix factorization to identify the layout of presynaptic bipolar cell inputs onto retinal ganglion cells and predict their responses to natural stimuli.

Loss of Neuroligin3 specifically downregulates retinal GABAAα2 receptors without abolishing direction selectivity

The postsynaptic adhesion proteins Neuroligins (NLs) are essential for proper synapse function, and their alterations are associated with a variety of neurodevelopmental disorders. It is increasingly clear that each NL isoform occupies specific subsets of synapses and is able to regulate the function of discrete networks. Studies of NL2 and NL4 in the retina in particular have contributed towards uncovering their role in inhibitory synapse function. In this study we show that NL3 is also predominantly expressed at inhibitory postsynapses in the retinal inner plexiform layer (IPL), where it colocalizes with both GABAA- and glycinergic receptor clusters in a 3:2 ratio. In the NL3 deletion-mutant (knockout or KO) mouse, we uncovered a dramatic reduction of the number of GABAAα2-subunit containing GABAA receptor clusters at the IPL. Retinal activity was thereafter assessed in KO and wild-type (WT) littermates by multi-electrode-array recordings of the output cells of retina, the retinal ganglion cells (RGCs). RGCs in the NL3 KO showed reduced spontaneous activity and an altered response to white noise stimulation. Moreover, upon application of light flashes, the proportion of cells firing at light offset (OFF RGCs) was significantly lower in the NL3 KO compared to WT littermates, whereas the relative number of cells firing at light onset (ON RGCs) increased. Interestingly, although GABAAα2-bearing receptors have been related to direction-selective circuits of the retina, features of direction selective-retinal ganglion cells recorded remained unperturbed in the NL3 KO. Together our data underscore the importance of NL3 for the integrity of specific GABAAergic retinal circuits and identifies NL3 as an important regulator of retinal activity.