Linear and nonlinear chromatic integration in the mouse retina

Filter-based models of suppression in retinal ganglion cells: Comparison and generalization across species and stimuli

The dichotomy of excitation and suppression is one of the canonical mechanisms explaining the complexity of neural activity. Computational models of the interplay of excitation and suppression in single neurons aim at investigating how this interaction affects a neuron's spiking responses and shapes the encoding of sensory stimuli. Here, we compare the performance of three filter-based stimulus-encoding models for predicting retinal ganglion cell responses recorded from axolotl, mouse, and marmoset retina to different types of temporally varying visual stimuli. Suppression in these models is implemented via subtractive or divisive interactions of stimulus filters or by a response-driven feedback module. For the majority of ganglion cells, the subtractive and divisive models perform similarly and outperform the feedback model as well as a linear-nonlinear (LN) model with no suppression. Comparison between the subtractive and the divisive model depends on cell type, species, and stimulus components, with the divisive model generalizing best across temporal stimulus frequencies and visual contrast and the subtractive model capturing in particular responses for slow temporal stimulus dynamics and for slow axolotl cells. Overall, we conclude that the divisive and subtractive models are well suited for capturing interactions of excitation and suppression in ganglion cells and perform best for different temporal regimes of these interactions.

Double-opponent spiking neuron array with orientation selectivity for encoding and spatial-chromatic processing

Color spiking encoding and opponent preprocessing are critical for energy-efficient object perception in the human visual system. Emulating the retina and brain's integration of spatial and chromatic spiking signals holds promise for enhancing the efficiency of vision sensors. Here, we introduce an artificial visual neuron array that generates excitatory or inhibitory spiking responses to specific wavelengths with orientation selectivity. The neuron array can function as double-opponent receptive fields for spatial-chromatic opponent preprocessing to color signals, emulating the neural pathway from the retina to the cortex. With the color spiking preprocessing function of the neuron array, the recognition accuracy is improved almost twofold compared to direct perception of underexposure objects, and the noise robustness is also strengthened. This architecture leverages biological mechanisms for simultaneous spike encoding and antagonistic preprocessing of color information, offering the potential for highly efficient neuromorphic vision systems.

GABAergic amacrine cells balance biased chromatic information in the mouse retina

The retina extracts chromatic information present in an animal's environment. How this information is processed in the retina is not well understood. In the mouse, chromatic information is not collected equally throughout the retina. Green and UV signals are primarily detected in the dorsal and ventral retina, respectively. However, at the output of the retina, chromatic tuning is more mixed throughout the retina. This suggests that lateral processing by inhibitory amacrine cells shapes chromatic information at the retinal output. We systematically surveyed the chromatic responses of dendritic processes of the 40+ GABAergic amacrine cell types. We identified 25 functional types with distinct chromatic and achromatic properties. We used pharmacology and a biologically inspired deep learning model to explore how inhibition and excitation shape the properties of functional types. Our data suggest that amacrine cells balance the biased spectral tuning of excitation, thereby supporting diversity of chromatic information at the retinal output.

A chromatic feature detector in the retina signals visual context changes

The retina transforms patterns of light into visual feature representations supporting behaviour. These representations are distributed across various types of retinal ganglion cells (RGCs), whose spatial and temporal tuning properties have been studied extensively in many model organisms, including the mouse. However, it has been difficult to link the potentially nonlinear retinal transformations of natural visual inputs to specific ethological purposes. Here, we discover a nonlinear selectivity to chromatic contrast in an RGC type that allows the detection of changes in visual context. We trained a convolutional neural network (CNN) model on large-scale functional recordings of RGC responses to natural mouse movies, and then used this model to search in silico for stimuli that maximally excite distinct types of RGCs. This procedure predicted centre colour opponency in transient suppressed-by-contrast (tSbC) RGCs, a cell type whose function is being debated. We confirmed experimentally that these cells indeed responded very selectively to Green-OFF, UV-ON contrasts. This type of chromatic contrast was characteristic of transitions from ground to sky in the visual scene, as might be elicited by head or eye movements across the horizon. Because tSbC cells performed best among all RGC types at reliably detecting these transitions, we suggest a role for this RGC type in providing contextual information (i.e. sky or ground) necessary for the selection of appropriate behavioural responses to other stimuli, such as looming objects. Our work showcases how a combination of experiments with natural stimuli and computational modelling allows discovering novel types of stimulus selectivity and identifying their potential ethological relevance.

Asymmetric distribution of color-opponent response types across mouse visual cortex supports superior color vision in the sky

Color is an important visual feature that informs behavior, and the retinal basis for color vision has been studied across various vertebrate species. While many studies have investigated how color information is processed in visual brain areas of primate species, we have limited understanding of how it is organized beyond the retina in other species, including most dichromatic mammals. In this study, we systematically characterized how color is represented in the primary visual cortex (V1) of mice. Using large-scale neuronal recordings and a luminance and color noise stimulus, we found that more than a third of neurons in mouse V1 are color-opponent in their receptive field center, while the receptive field surround predominantly captures luminance contrast. Furthermore, we found that color-opponency is especially pronounced in posterior V1 that encodes the sky, matching the statistics of natural scenes experienced by mice. Using unsupervised clustering, we demonstrate that the asymmetry in color representations across cortex can be explained by an uneven distribution of green-On/UV-Off color-opponent response types that are represented in the upper visual field. Finally, a simple model with natural scene-inspired parametric stimuli shows that green-On/UV-Off color-opponent response types may enhance the detection of 'predatory'-like dark UV-objects in noisy daylight scenes. The results from this study highlight the relevance of color processing in the mouse visual system and contribute to our understanding of how color information is organized in the visual hierarchy across species.

Context and space coding in mossy cell population activity

The dentate gyrus plays a key role in the discrimination of memories by segregating and storing similar episodes. Whether hilar mossy cells, which constitute a major excitatory principal cell type in the mammalian hippocampus, contribute to this decorrelation function has remained largely unclear. Using two-photon calcium imaging of head-fixed mice performing a spatial virtual reality task, we show that mossy cell populations robustly discriminate between familiar and novel environments. The degree of discrimination depends on the extent of visual cue differences between contexts. A context decoder revealed that successful environmental classification is explained mainly by activity difference scores of mossy cells. By decoding mouse position, we reveal that in addition to place cells, the coordinated activity among active mossy cells markedly contributes to the encoding of space. Thus, by decorrelating context information according to the degree of environmental differences, mossy cell populations support pattern separation processes within the dentate gyrus.

Different spectral sensitivities of ON- and OFF-motion pathways enhance the detection of approaching color objects in Drosophila

Color and motion are used by many species to identify salient objects. They are processed largely independently, but color contributes to motion processing in humans, for example, enabling moving colored objects to be detected when their luminance matches the background. Here, we demonstrate an unexpected, additional contribution of color to motion vision in Drosophila. We show that behavioral ON-motion responses are more sensitive to UV than for OFF-motion, and we identify cellular pathways connecting UV-sensitive R7 photoreceptors to ON and OFF-motion-sensitive T4 and T5 cells, using neurogenetics and calcium imaging. Remarkably, this contribution of color circuitry to motion vision enhances the detection of approaching UV discs, but not green discs with the same chromatic contrast, and we show how this could generalize for systems with ON- and OFF-motion pathways. Our results provide a computational and circuit basis for how color enhances motion vision to favor the detection of saliently colored objects.

Molecular Mechanisms Mediating the Transfer of Disease-Associated Proteins and Effects on Neuronal Activity

BACKGROUND

Various cellular pathways have been implicated in the transfer of disease-related proteins between cells, contributing to disease progression and neurodegeneration. However, the overall effects of protein transfer are still unclear.

OBJECTIVE

Here, we performed a systematic comparison of basic molecular mechanisms involved in the release of alpha-synuclein, Tau, and huntingtin, and evaluated functional effects upon internalization by receiving cells.

METHODS

Evaluation of protein release to the extracellular space in a free form and in extracellular vesicles using an optimized ultracentrifugation protocol. The extracellular effects of the proteins and extracellular vesicles in primary neuronal cultures were assessed using multi-channel electrophysiological recordings combined with a customized spike sorting framework.

RESULTS

We demonstrate cells differentially release free-forms of each protein to the extracellular space. Importantly, neuronal activity is distinctly modulated upon protein internalization in primary cortical cultures. In addition, these disease-related proteins also occur in extracellular vesicles, and are enriched in ectosomes. Internalization of ectosomes and exosomes by primary microglial or astrocytic cells elicits the production of pro-inflammatory cytokines, and modifies spontaneous electrical activity in neurons.

OBJECTIVE

Overall, our study demonstrates that released proteins can have detrimental effects for surrounding cells, and suggests protein release pathways may be exploited as therapeutic targets in different neurodegenerative diseases.

Ectosomes and exosomes modulate neuronal spontaneous activity

Extracellular vesicles (EVs) are important mediators in intercellular communication. However, understanding the biological origin and functional effects of EVs subtypes has been challenging due to the moderate differences in their physical properties and absence of reliable markers. Here, we characterize the proteomes of ectosomes and exosomes using an improved differential ultracentrifugation protocol and quantitative proteomics. Our analyses revealed singular proteomic profiles for ectosomes and exosomes that enabled us to establish specific protein markers that can be used for their biochemical distinction. Cytoskeleton and glycolytic proteins are distinctively present in ectosomes, while endosomal sorting complexes proteins and tetraspanins are enriched in exosomes. Furthermore, annexin-A2 was identified as a specific marker for ectosomes derived from cell media and human cerebrospinal fluid. Expression of EGFP as a cytosolic reporter leads to its incorporation in EVs and enables their imaging with higher resolution. Assessment of neuronal network activity using multi-electrode array recordings demonstrated that spontaneous neuronal activity can be modulated by EVs. Ectosomes and exosomes internalization in neuronal cells disrupted their regular synchronized bursting activity, resulting in overall lower and more disorganized spiking activity. Our findings suggest that EVs cargoes reflect core intracellular processes, and their functional properties might regulate basic biological and pathological processes. SIGNIFICANCE: This article presents novel approaches for studying the origin, composition, and biological effects in neuronal activity of ectosomes and exosomes. Our findings suggest that EVs cargoes reflect core intracellular processes, and their functional properties might regulate basic biological and pathological processes. Ultimately, our study also forms the foundation for future biomarker studies and for the understanding of the molecular basis of different diseases.

Retinal Encoding of Natural Scenes

An ultimate goal in retina science is to understand how the neural circuit of the retina processes natural visual scenes. Yet most studies in laboratories have long been performed with simple, artificial visual stimuli such as full-field illumination, spots of light, or gratings. The underlying assumption is that the features of the retina thus identified carry over to the more complex scenario of natural scenes. As the application of corresponding natural settings is becoming more commonplace in experimental investigations, this assumption is being put to the test and opportunities arise to discover processing features that are triggered by specific aspects of natural scenes. Here, we review how natural stimuli have been used to probe, refine, and complement knowledge accumulated under simplified stimuli, and we discuss challenges and opportunities along the way toward a comprehensive understanding of the encoding of natural scenes. Expected final online publication date for the Annual Review of Vision Science, Volume 8 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Simple model for encoding natural images by retinal ganglion cells with nonlinear spatial integration

A central goal in sensory neuroscience is to understand the neuronal signal processing involved in the encoding of natural stimuli. A critical step towards this goal is the development of successful computational encoding models. For ganglion cells in the vertebrate retina, the development of satisfactory models for responses to natural visual scenes is an ongoing challenge. Standard models typically apply linear integration of visual stimuli over space, yet many ganglion cells are known to show nonlinear spatial integration, in particular when stimulated with contrast-reversing gratings. We here study the influence of spatial nonlinearities in the encoding of natural images by ganglion cells, using multielectrode-array recordings from isolated salamander and mouse retinas. We assess how responses to natural images depend on first- and second-order statistics of spatial patterns inside the receptive field. This leads us to a simple extension of current standard ganglion cell models. We show that taking not only the weighted average of light intensity inside the receptive field into account but also its variance over space can partly account for nonlinear integration and substantially improve response predictions of responses to novel images. For salamander ganglion cells, we find that response predictions for cell classes with large receptive fields profit most from including spatial contrast information. Finally, we demonstrate how this model framework can be used to assess the spatial scale of nonlinear integration. Our results underscore that nonlinear spatial stimulus integration translates to stimulation with natural images. Furthermore, the introduced model framework provides a simple, yet powerful extension of standard models and may serve as a benchmark for the development of more detailed models of the nonlinear structure of receptive fields.

For understanding how sensory systems operate in the natural environment, an important goal is to develop models that capture neuronal responses to natural stimuli. For retinal ganglion cells, which connect the eye to the brain, current standard models often fail to capture responses to natural visual scenes. This shortcoming is at least partly rooted in the fact that ganglion cells may combine visual signals over space in a nonlinear fashion. We here show that a simple model, which not only considers the average light intensity inside a cell’s receptive field but also the variance of light intensity over space, can partly account for these nonlinearities and thereby improve current standard models. This provides an easy-to-obtain benchmark for modeling ganglion cell responses to natural images.

Spectral inference reveals principal cone-integration rules of the zebrafish inner retina

Retinal bipolar cells integrate cone signals at dendritic and axonal sites. The axonal route, involving amacrine cells, remains largely uncharted. However, because cone types differ in their spectral sensitivities, insights into bipolar cells' cone integration might be gained based on their spectral tunings. We therefore recorded in vivo responses of bipolar cell presynaptic terminals in larval zebrafish to widefield but spectrally resolved flashes of light and mapped the results onto spectral responses of the four cones. This "spectral circuit mapping" allowed explaining ∼95% of the spectral and temporal variance of bipolar cell responses in a simple linear model, thereby revealing several notable integration rules of the inner retina. Bipolar cells were dominated by red-cone inputs, often alongside equal sign inputs from blue and green cones. In contrast, UV-cone inputs were uncorrelated with those of the remaining cones. This led to a new axis of spectral opponency where red-, green-, and blue-cone "Off" circuits connect to "natively-On" UV-cone circuits in the outermost fraction of the inner plexiform layer-much as how key color opponent circuits are established in mammals. Beyond this, and despite substantial temporal diversity that was not present in the cones, bipolar cell spectral tunings were surprisingly simple. They either approximately resembled both opponent and non-opponent spectral motifs already present in the cones or exhibited a stereotyped non-opponent broadband response. In this way, bipolar cells not only preserved the efficient spectral representations in the cones but also diversified them to set up a total of six dominant spectral motifs, which included three axes of spectral opponency.

Natural environment statistics in the upper and lower visual field are reflected in mouse retinal specializations

Pressures for survival make sensory circuits adapted to a species' natural habitat and its behavioral challenges. Thus, to advance our understanding of the visual system, it is essential to consider an animal's specific visual environment by capturing natural scenes, characterizing their statistical regularities, and using them to probe visual computations. Mice, a prominent visual system model, have salient visual specializations, being dichromatic with enhanced sensitivity to green and UV in the dorsal and ventral retina, respectively. However, the characteristics of their visual environment that likely have driven these adaptations are rarely considered. Here, we built a UV-green-sensitive camera to record footage from mouse habitats. This footage is publicly available as a resource for mouse vision research. We found chromatic contrast to greatly diverge in the upper, but not the lower, visual field. Moreover, training a convolutional autoencoder on upper, but not lower, visual field scenes was sufficient for the emergence of color-opponent filters, suggesting that this environmental difference might have driven superior chromatic opponency in the ventral mouse retina, supporting color discrimination in the upper visual field. Furthermore, the upper visual field was biased toward dark UV contrasts, paralleled by more light-offset-sensitive ganglion cells in the ventral retina. Finally, footage recorded at twilight suggests that UV promotes aerial predator detection. Our findings support that natural scene statistics shaped early visual processing in evolution.

Interphotoreceptor coupling: an evolutionary perspective

In the vertebrate retina, signals generated by cones of different spectral preference and by highly sensitive rod photoreceptors interact at various levels to extract salient visual information. The first opportunity for such interaction is offered by electrical coupling of the photoreceptors themselves, which is mediated by gap junctions located at the contact points of specialised cellular processes: synaptic terminals, telodendria and radial fins. Here, we examine the evolutionary pressures for and against interphotoreceptor coupling, which are likely to have shaped how coupling is deployed in different species. The impact of coupling on signal to noise ratio, spatial acuity, contrast sensitivity, absolute and increment threshold, retinal signal flow and colour discrimination is discussed while emphasising available data from a variety of vertebrate models spanning from lampreys to primates. We highlight the many gaps in our knowledge, persisting discrepancies in the literature, as well as some major unanswered questions on the actual extent and physiological role of cone-cone, rod-cone and rod-rod communication. Lastly, we point toward limited but intriguing evidence suggestive of the ancestral form of coupling among ciliary photoreceptors.