Complex Visual Motion Representation in Mouse Area V1

A systematic analysis of the joint effects of ganglion cells, lagged LGN cells, and intercortical inhibition on spatiotemporal processing and direction selectivity

Simple cells in the visual cortex process spatial as well as temporal information of the visual stream and enable the perception of motion information. Previous work suggests different mechanisms associated with direction selectivity, such as a temporal offset in thalamocortical input stream through lagged and non-lagged cells of the lateral geniculate nucleus (LGN), or solely from intercortical inhibition, or through a baseline selectivity provided by the thalamocortical connection tuned by intercortical inhibition. While there exists a large corpus of models for spatiotemporal receptive fields, the majority of them built-in the spatiotemporal dynamics by utilizing a combination of spatial and temporal functions and thus, do not explain the emergence of spatiotemporal dynamics on basis of network dynamics emerging in the retina and the LGN. In order to better comprehend the emergence of spatiotemporal processing and direction selectivity, we used a spiking neural network to implement the visual pathway from the retina to the primary visual cortex. By varying different functional parts in our network, we demonstrate how the direction selectivity of simple cells emerges through the interplay between two components: tuned intercortical inhibition and a temporal offset in the feedforward path through lagged LGN cells. In contrast to previous findings, our model simulations suggest an alternative dynamic between these two mechanisms: While intercortical inhibition alone leads to bidirectional selectivity, a temporal shift in the thalamocortical pathway breaks this symmetry in favor of one direction, leading to unidirectional selectivity.

A burst-dependent thalamocortical substrate for perceptual awareness

Contemporary models of perceptual awareness lack tractable neurobiological constraints. Inspired by recent cellular recordings in a mouse model of tactile threshold detection, we constructed a biophysical model of perceptual awareness that incorporated essential features of thalamocortical anatomy and cellular physiology. Our model reproduced, and mechanistically explains, the key in vivo neural and behavioural signatures of perceptual awareness in the mouse model, as well as the response to a set of causal perturbations. We generalised the same model (with identical parameters) to a more complex task - visual rivalry - and found that the same thalamic-mediated mechanism of perceptual awareness determined perceptual dominance. This led to the generation of a set of novel, and directly testable, electrophysiological predictions. Analyses of the model based on dynamical systems theory show that perceptual awareness in simulations of both threshold detection and visual rivalry arises from the emergent systems-level dynamics of thalamocortical loops.

Broadband visual stimuli improve neuronal representation and sensory perception

Natural scenes consist of complex feature distributions that shape neural responses and perception. However, in contrast to single features like stimulus orientations, the impact of broadband feature distributions remains unclear. We, therefore, presented visual stimuli with parametrically-controlled bandwidths of orientations and spatial frequencies to awake mice while recording neural activity in their primary visual cortex (V1). Increasing orientation but not spatial frequency bandwidth strongly increased the number and response amplitude of V1 neurons. This effect was not explained by single-cell orientation tuning but rather a broadband-specific relief from center-surround suppression. Moreover, neurons in deeper V1 and the superior colliculus responded much stronger to broadband stimuli, especially when mixing orientations and spatial frequencies. Lastly, broadband stimuli increased the separability of neural responses and improved the performance of mice in a visual discrimination task. Our results show that surround modulation increases neural responses to complex natural feature distributions to enhance sensory perception.

Feature selectivity and invariance in marsupial primary visual cortex

A fundamental question in sensory neuroscience revolves around how neurons represent complex visual stimuli. In mammalian primary visual cortex (V1), neurons decode intricate visual features to identify objects, with most being selective for edge orientation, but with half of those also developing invariance to edge position within their receptive fields. Position invariance allows cells to continue to code an edge even when it moves around. Combining feature selectivity and invariance is integral to successful object recognition. Considering the marsupial-eutherian divergence 160 million years ago, we explored whether feature selectivity and invariance was similar in marsupials and eutherians. We recovered the spatial filters and non-linear processing characteristics of the receptive fields of neurons in wallaby V1 and compared them with previous results from cat cortex. We stimulated the neurons in V1 with white Gaussian noise and analysed responses using the non-linear input model. Wallabies exhibit the same high percentage of orientation selective neurons as cats. However, in wallabies we observed a notably higher prevalence of neurons with three or more filters compared to cats. We show that having three or more filters substantially increases phase invariance in the V1s of both species, but that wallaby V1 accentuates this feature, suggesting that the species condenses more processing into the earliest cortical stage. These findings suggest that evolution has led to more than one solution to the problem of creating complex visual processing strategies. KEY POINTS: Previous studies have shown that the primary visual cortex (V1) in mammals is essential for processing complex visual stimuli, with neurons displaying selectivity for edge orientation and position. This research explores whether the visual processing mechanisms in marsupials, such as wallabies, are similar to those in eutherian mammals (e.g. cats). The study found that wallabies have a higher prevalence of neurons with multiple spatial filters in V1, indicating more complex visual processing. Using a non-linear input model, we demonstrated that neurons with three or more filters increase phase invariance. These findings suggest that marsupials and eutherian mammals have evolved similar strategies for visual processing, but marsupials have condensed more capacity to build phase invariance into the first step in the cortical pathway.

The superior colliculus: New insights into an evolutionarily ancient structure

The superior colliculus is a structure located in the dorsal midbrain with well conserved function and connectivity across species. Essential for survival, the superior colliculus has evolved to trigger rapid orientation and avoidance movements in response to external stimuli. The increasing recognition of the widespread connectivity of the superior colliculus, not only with brainstem and spinal cord, but also with virtually all brain structures, has rekindled the interest on this structure and revealed novel roles in the past few years. In this review, we focus on the most recent advancements in understanding its cellular composition, connectivity and function, with a particular focus on how the cellular diversity and connectivity arises during development, as well as on its recent role in the emergence of sensory circuits.

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.

Thalamic contributions to the state and contents of consciousness

Consciousness can be conceptualized as varying along at least two dimensions: the global state of consciousness and the content of conscious experience. Here, we highlight the cellular and systems-level contributions of the thalamus to conscious state and then argue for thalamic contributions to conscious content, including the integrated, segregated, and continuous nature of our experience. We underscore vital, yet distinct roles for core- and matrix-type thalamic neurons. Through reciprocal interactions with deep-layer cortical neurons, matrix neurons support wakefulness and determine perceptual thresholds, whereas the cortical interactions of core neurons maintain content and enable perceptual constancy. We further propose that conscious integration, segregation, and continuity depend on the convergent nature of corticothalamic projections enabling dimensionality reduction, a thalamic reticular nucleus-mediated divisive normalization-like process, and sustained coherent activity in thalamocortical loops, respectively. Overall, we conclude that the thalamus plays a central topological role in brain structures controlling conscious experience.

The meso-connectomes of mouse, marmoset, and macaque: network organization and the emergence of higher cognition

The recent publications of the inter-areal connectomes for mouse, marmoset, and macaque cortex have allowed deeper comparisons across rodent vs. primate cortical organization. In general, these show that the mouse has very widespread, "all-to-all" inter-areal connectivity (i.e. a "highly dense" connectome in a graph theoretical framework), while primates have a more modular organization. In this review, we highlight the relevance of these differences to function, including the example of primary visual cortex (V1) which, in the mouse, is interconnected with all other areas, therefore including other primary sensory and frontal areas. We argue that this dense inter-areal connectivity benefits multimodal associations, at the cost of reduced functional segregation. Conversely, primates have expanded cortices with a modular connectivity structure, where V1 is almost exclusively interconnected with other visual cortices, themselves organized in relatively segregated streams, and hierarchically higher cortical areas such as prefrontal cortex provide top-down regulation for specifying precise information for working memory storage and manipulation. Increased complexity in cytoarchitecture, connectivity, dendritic spine density, and receptor expression additionally reveal a sharper hierarchical organization in primate cortex. Together, we argue that these primate specializations permit separable deconstruction and selective reconstruction of representations, which is essential to higher cognition.

Tug-of-Peace: Visual Rivalry and Atypical Visual Motion Processing in MECP2 Duplication Syndrome of Autism

Extracting common patterns of neural circuit computations in the autism spectrum and confirming them as a cause of specific core traits of autism is the first step toward identifying cell-level and circuit-level targets for effective clinical intervention. Studies in humans with autism have identified functional links and common anatomic substrates between core restricted behavioral repertoire, cognitive rigidity, and overstability of visual percepts during visual rivalry. To study these processes with single-cell precision and comprehensive neuronal population coverage, we developed the visual bistable perception paradigm for mice based on ambiguous moving plaid patterns consisting of two transparent gratings drifting at an angle of 120°. This results in spontaneous reversals of the perception between local component motion (plaid perceived as two separate moving grating components) and integrated global pattern motion (plaid perceived as a fused moving texture). This robust paradigm does not depend on the explicit report of the mouse, since the direction of the optokinetic nystagmus (OKN) is used to infer the dominant percept. Using this paradigm, we found that the rate of perceptual reversals between global and local motion interpretations is reduced in the methyl-CpG-binding protein 2 duplication syndrome (MECP2-ds) mouse model of autism. Moreover, the stability of local motion percepts is greatly increased in MECP2-ds mice at the expense of global motion percepts. Thus, our model reproduces a subclass of the core features in human autism (reduced rate of visual rivalry and atypical perception of visual motion). This further offers a well-controlled approach for dissecting neuronal circuits underlying these core features.

Truly pattern: Nonlinear integration of motion signals is required to account for the responses of pattern cells in rat visual cortex

A key feature of advanced motion processing in the primate dorsal stream is the existence of pattern cells-specialized cortical neurons that integrate local motion signals into pattern-invariant representations of global direction. Pattern cells have also been reported in rodent visual cortex, but it is unknown whether the tuning of these neurons results from truly integrative, nonlinear mechanisms or trivially arises from linear receptive fields (RFs) with a peculiar geometry. Here, we show that pattern cells in rat primary (V1) and lateromedial (LM) visual cortex process motion direction in a way that cannot be explained by the linear spatiotemporal structure of their RFs. Instead, their tuning properties are consistent with and well explained by those of units in a state-of-the-art neural network model of the dorsal stream. This suggests that similar cortical processes underlay motion representation in primates and rodents. The latter could thus serve as powerful model systems to unravel the underlying circuit-level mechanisms.

Differential encoding of temporally evolving color patterns across nearby V1 neurons

Whereas studies of the V1 cortex have focused mainly on neural line orientation preference, color inputs are also known to have a strong presence among these neurons. Individual neurons typically respond to multiple colors and nearby neurons have different combinations of preferred color inputs. However, the computations performed by V1 neurons on such color inputs have not been extensively studied. Here we aimed to address this issue by studying how different V1 neurons encode different combinations of inputs composed of four basic colors. We quantified the decoding accuracy of individual neurons from multi-electrode array recordings, comparing multiple individual neurons located within 2 mm along the vertical axis of the V1 cortex of the anesthetized rat. We found essentially all V1 neurons to be good at decoding spatiotemporal patterns of color inputs and they did so by encoding them in different ways. Quantitative analysis showed that even adjacent neurons encoded the specific input patterns differently, suggesting a local cortical circuitry organization which tends to diversify rather than unify the neuronal responses to each given input. Using different pairs of monocolor inputs, we also found that V1 neocortical neurons had a diversified and rich color opponency across the four colors, which was somewhat surprising given the fact that rodent retina express only two different types of opsins. We propose that the processing of color inputs in V1 cortex is extensively composed of multiple independent circuitry components that reflect abstract functionalities resident in the internal cortical processing rather than the raw sensory information per se.

Hierarchical temporal prediction captures motion processing along the visual pathway

Visual neurons respond selectively to features that become increasingly complex from the eyes to the cortex. Retinal neurons prefer flashing spots of light, primary visual cortical (V1) neurons prefer moving bars, and those in higher cortical areas favor complex features like moving textures. Previously, we showed that V1 simple cell tuning can be accounted for by a basic model implementing temporal prediction - representing features that predict future sensory input from past input (Singer et al., 2018). Here, we show that hierarchical application of temporal prediction can capture how tuning properties change across at least two levels of the visual system. This suggests that the brain does not efficiently represent all incoming information; instead, it selectively represents sensory inputs that help in predicting the future. When applied hierarchically, temporal prediction extracts time-varying features that depend on increasingly high-level statistics of the sensory input.

Visual evoked potentials waveform analysis to measure intracortical damage in a preclinical model of multiple sclerosis

Introduction

Visual evoked potentials (VEPs) are a non-invasive technique routinely used in clinical and preclinical practice. Discussion about inclusion of VEPs in McDonald criteria, used for Multiple Sclerosis (MS) diagnosis, increased the importance of VEP in MS preclinical models. While the interpretation of the N1 peak is recognized, less is known about the first and second positive VEP peaks, P1 and P2, and the implicit time of the different segments. Our hypothesis is that P2 latency delay describes intracortical neurophysiological dysfunction from the visual cortex to the other cortical areas.

Methods

In this work, we analyzed VEP traces that were included in our two recently published papers on Experimental Autoimmune Encephalomyelitis (EAE) mouse model. Compared with these previous publications other VEP peaks, P1 and P2, and the implicit time of components P1-N1, N1-P2 and P1-P2, were analyzed in blind.

Results

Latencies of P2, P1-P2, P1-N1 and N1-P2 were increased in all EAE mice, including group without N1 latency change delay at early time points. In particular, at 7 dpi the P2 latency delay change was significantly higher compared with N1 latency change delay. Moreover, new analysis of these VEP components under the influence of neurostimulation revealed a decrease in P2 delay in stimulated animals.

Discussion

P2 latency delay, P1-P2, P1-N1, and N1-P2 latency changes which reflect intracortical dysfunction, were consistently detected across all EAE groups before N1 change. Results underline the importance of analyzing all VEP components for a complete overview of the neurophysiological visual pathway dysfunction and treatment efficacy.

Feedforward mechanisms of cross-orientation interactions in mouse V1

Sensory neurons are modulated by context. For example, in mouse primary visual cortex (V1), neuronal responses to the preferred orientation are modulated by the presence of superimposed orientations ("plaids"). The effects of this modulation are diverse; some neurons are suppressed, while others have larger responses to a plaid than its components. We investigated whether this diversity could be explained by a unified circuit mechanism. We report that this masking is maintained during suppression of cortical activity, arguing against cortical mechanisms. Instead, the heterogeneity of plaid responses is explained by an interaction between stimulus geometry and orientation tuning. Highly selective neurons are uniformly suppressed by plaids, whereas the effects in weakly selective neurons depend on the spatial configuration of the stimulus, transitioning systematically between suppression and facilitation. Thus, the diverse responses emerge as a consequence of the spatial structure of feedforward inputs, with no need to invoke cortical interactions.

Anatomical and functional connectomes underlying hierarchical visual processing in mouse visual system

Over the last 10 years, there has been a surge in interest in the rodent visual system resulting from the discovery of visual processing functions shared with primates V1, and of a complex anatomical structure in the extrastriate visual cortex. This surprisingly intricate visual system was elucidated by recent investigations using rapidly growing genetic tools primarily available in the mouse. Here, we examine the structural and functional connections of visual areas that have been identified in mice mostly during the past decade, and the impact of these findings on our understanding of brain functions associated with vision. Special attention is paid to structure-function relationships arising from the hierarchical organization, which is a prominent feature of the primate visual system. Recent evidence supports the existence of a hierarchical organization in rodents that contains levels that are poorly resolved relative to those observed in primates. This shallowness of the hierarchy indicates that the mouse visual system incorporates abundant non-hierarchical processing. Thus, the mouse visual system provides a unique opportunity to study non-hierarchical processing and its relation to hierarchical processing.

Visuomotor control in mice and primates

We conduct a comparative evaluation of the visual systems from the retina to the muscles of the mouse and the macaque monkey noting the differences and similarities between these two species. The topics covered include (1) visual-field overlap, (2) visual spatial resolution, (3) V1 cortical point-image [i.e., V1 tissue dedicated to analyzing a unit receptive field], (4) object versus motion encoding, (5) oculomotor range, (6) eye, head, and body movement coordination, and (7) neocortical and cerebellar function. We also discuss blindsight in rodents and primates which provides insights on how the neocortex mediates conscious vision in these species. This review is timely because the field of visuomotor neurophysiology is expanding beyond the macaque monkey to include the mouse; there is therefore a need for a comparative analysis between these two species on how the brain generates visuomotor responses.

Rats spontaneously perceive global motion direction of drifting plaids

Computing global motion direction of extended visual objects is a hallmark of primate high-level vision. Although neurons selective for global motion have also been found in mouse visual cortex, it remains unknown whether rodents can combine multiple motion signals into global, integrated percepts. To address this question, we trained two groups of rats to discriminate either gratings (G group) or plaids (i.e., superpositions of gratings with different orientations; P group) drifting horizontally along opposite directions. After the animals learned the task, we applied a visual priming paradigm, where presentation of the target stimulus was preceded by the brief presentation of either a grating or a plaid. The extent to which rat responses to the targets were biased by such prime stimuli provided a measure of the spontaneous, perceived similarity between primes and targets. We found that gratings and plaids, when used as primes, were equally effective at biasing the perception of plaid direction for the rats of the P group. Conversely, for the G group, only the gratings acted as effective prime stimuli, while the plaids failed to alter the perception of grating direction. To interpret these observations, we simulated a decision neuron reading out the representations of gratings and plaids, as conveyed by populations of either component or pattern cells (i.e., local or global motion detectors). We concluded that the findings for the P group are highly consistent with the existence of a population of pattern cells, playing a functional role similar to that demonstrated in primates. We also explored different scenarios that could explain the failure of the plaid stimuli to elicit a sizable priming magnitude for the G group. These simulations yielded testable predictions about the properties of motion representations in rodent visual cortex at the single-cell and circuitry level, thus paving the way to future neurophysiology experiments.

Visual motion integration of bidirectional transparent motion in mouse opto-locomotor reflexes

Visual motion perception depends on readout of direction selective sensors. We investigated in mice whether the response to bidirectional transparent motion, activating oppositely tuned sensors, reflects integration (averaging) or winner-take-all (mutual inhibition) mechanisms. We measured whole body opto-locomotor reflexes (OLRs) to bidirectional oppositely moving random dot patterns (leftward and rightward) and compared the response to predictions based on responses to unidirectional motion (leftward or rightward). In addition, responses were compared to stimulation with stationary patterns. When comparing OLRs to bidirectional and unidirectional conditions, we found that the OLR to bidirectional motion best fits an averaging model. These results reflect integration mechanisms in neural responses to contradicting sensory evidence as has been documented for other sensory and motor domains.

Retino-Cortical Mapping Ratio Predicts Columnar and Salt-and-Pepper Organization in Mammalian Visual Cortex

In the mammalian primary visual cortex, neural tuning to stimulus orientation is organized in either columnar or salt-and-pepper patterns across species. For decades, this sharp contrast has spawned fundamental questions about the origin of functional architectures in visual cortex. However, it is unknown whether these patterns reflect disparate developmental mechanisms across mammalian taxa or simply originate from variation of biological parameters under a universal development process. In this work, after the analysis of data from eight mammalian species, we show that cortical organization is predictable by a single factor, the retino-cortical mapping ratio. Groups of species with or without columnar clustering are distinguished by the feedforward sampling ratio, and model simulations with controlled mapping conditions reproduce both types of organization. Prediction from the Nyquist theorem explains this parametric division of the patterns with high accuracy. Our results imply that evolutionary variation of physical parameters may induce development of distinct functional circuitry.

Visual Response Characteristics in Lateral and Medial Subdivisions of the Rat Pulvinar

The pulvinar is a higher-order thalamic relay and a central component of the extrageniculate visual pathway, with input from the superior colliculus and visual cortex and output to all of visual cortex. Rodent pulvinar, more commonly called the lateral posterior nucleus (LP), consists of three highly-conserved subdivisions, and offers the advantage of simplicity in its study compared to more subdivided primate pulvinar. Little is known about receptive field properties of LP, let alone whether functional differences exist between different LP subdivisions, making it difficult to understand what visual information is relayed and what kinds of computations the pulvinar might support. Here, we characterized single-cell response properties in two V1 recipient subdivisions of rat pulvinar, the rostromedial (LPrm) and lateral (LPl), and found that a fourth of the cells were selective for orientation, compared to half in V1, and that LP tuning widths were significantly broader. Response latencies were also significantly longer and preferred size more than three times larger on average than in V1; the latter suggesting pulvinar as a source of spatial context to V1. Between subdivisons, LPl cells preferred higher temporal frequencies, whereas LPrm showed a greater degree of direction selectivity and pattern motion detection. Taken together with known differences in connectivity patterns, these results suggest two separate visual feature processing channels in the pulvinar, one in LPl related to higher speed processing which likely derives from superior colliculus input, and the other in LPrm for motion processing derived through input from visual cortex. SIGNIFICANCE STATEMENT: The pulvinar has a perplexing role in visual cognition as no clear link has been found between the functional properties of its neurons and behavioral deficits that arise when it is damaged. The pulvinar, called the lateral posterior nucleus (LP) in rats, is a higher order thalamic relay with input from the superior colliculus and visual cortex and output to all of visual cortex. By characterizing single-cell response properties in anatomically distinct subdivisions we found two separate visual feature processing channels in the pulvinar, one in lateral LP related to higher speed processing which likely derives from superior colliculus input, and the other in rostromedial LP for motion processing derived through input from visual cortex.

Distributed and retinotopically asymmetric processing of coherent motion in mouse visual cortex

Perception of visual motion is important for a range of ethological behaviors in mammals. In primates, specific visual cortical regions are specialized for processing of coherent visual motion. However, whether mouse visual cortex has a similar organization remains unclear, despite powerful genetic tools available for measuring population neural activity. Here, we use widefield and 2-photon calcium imaging of transgenic mice to measure mesoscale and cellular responses to coherent motion. Imaging of primary visual cortex (V1) and higher visual areas (HVAs) during presentation of natural movies and random dot kinematograms (RDKs) reveals varied responsiveness to coherent motion, with stronger responses in dorsal stream areas compared to ventral stream areas. Moreover, there is considerable anisotropy within visual areas, such that neurons representing the lower visual field are more responsive to coherent motion. These results indicate that processing of visual motion in mouse cortex is distributed heterogeneously both across and within visual areas.

An Unexpected Dependence of Cortical Depth in Shaping Neural Responsiveness and Selectivity in Mouse Visual Cortex

Two-photon imaging studies in mouse primary visual cortex (V1) consistently report that around half of the neurons respond to oriented grating stimuli. However, in cats and primates, nearly all neurons respond to such stimuli. Here we show that mouse V1 responsiveness and selectivity strongly depends on neuronal depth. Moving from superficial layer 2 down to layer 4, the percentage of visually responsive neurons nearly doubled, ultimately reaching levels similar to what is seen in other species. Over this span, the amplitude of neuronal responses also doubled. Moreover, stimulus selectivity was also modulated, not only with depth but also with response amplitude. Specifically, we found that orientation and direction selectivity were greater in stronger responding neurons, but orientation selectivity decreased with depth whereas direction selectivity increased. Importantly, these depth-dependent trends were found not just between layer 2/3 and layer 4 but at different depths within layer 2/3 itself. Thus, neuronal depth is an important factor to consider when pooling neurons for population analyses. Furthermore, the inability to drive the majority of cells in superficial layer 2/3 of mouse V1 with grating stimuli indicates that there may be fundamental differences in the micro-circuitry and role of V1 between rodents and other mammals.

A large-scale standardized physiological survey reveals functional organization of the mouse visual cortex

To understand how the brain processes sensory information to guide behavior, we must know how stimulus representations are transformed throughout the visual cortex. Here we report an open, large-scale physiological survey of activity in the awake mouse visual cortex: the Allen Brain Observatory Visual Coding dataset. This publicly available dataset includes the cortical activity of nearly 60,000 neurons from six visual areas, four layers, and 12 transgenic mouse lines in a total of 243 adult mice, in response to a systematic set of visual stimuli. We classify neurons on the basis of joint reliabilities to multiple stimuli and validate this functional classification with models of visual responses. While most classes are characterized by responses to specific subsets of the stimuli, the largest class is not reliably responsive to any of the stimuli and becomes progressively larger in higher visual areas. These classes reveal a functional organization wherein putative dorsal areas show specialization for visual motion signals.

The geometry of masking in neural populations

The normalization model provides an elegant account of contextual modulation in individual neurons of primary visual cortex. Understanding the implications of normalization at the population level is hindered by the heterogeneity of cortical neurons, which differ in the composition of their normalization pools and semi-saturation constants. Here we introduce a geometric approach to investigate contextual modulation in neural populations and study how the representation of stimulus orientation is transformed by the presence of a mask. We find that population responses can be embedded in a low-dimensional space and that an affine transform can account for the effects of masking. The geometric analysis further reveals a link between changes in discriminability and bias induced by the mask. We propose the geometric approach can yield new insights into the image processing computations taking place in early visual cortex at the population level while coping with the heterogeneity of single cell behavior.

The Visual Cortex in Context

In this article, we review the anatomical inputs and outputs to the mouse primary visual cortex, area V1. Our survey of data from the Allen Institute Mouse Connectivity project indicates that mouse V1 is highly interconnected with both cortical and subcortical brain areas. This pattern of innervation allows for computations that depend on the state of the animal and on behavioral goals, which contrasts with simple feedforward, hierarchical models of visual processing. Thus, to have an accurate description of the function of V1 during mouse behavior, its involvement with the rest of the brain circuitry has to be considered. Finally, it remains an open question whether the primary visual cortex of higher mammals displays the same degree of sensorimotor integration in the early visual system.

Inhibitory Units: An Organizing Nidus for Feature-Selective SubNetworks in Area V1

Neuronal circuits often display small-world network architecture characterized by neuronal cliques of dense local connectivity communicating with each other through a limited number of cells that participate in multiple cliques. The principles by which such cliques organize to encode information remain poorly understood. Similarly tuned pyramidal cells that preferentially target each other may form multicellular encoding units performing distinct computational tasks. The existence of such units can reflect upon both spontaneous and stimulus-driven population events.We applied two-photon calcium imaging to study spontaneous population bursts in layer 2/3 of area V1 in male C57BL/6 mice. To identify potential small-world cliques, we searched for pyramidal cells whose calcium events had a consistent temporal relationship with the events of local inhibitory interneurons. This was guided by the intuition that groups of neurons whose synchronous firing represents a temporally coherent computational unit should be inhibited together. Pyramidal members of these interneuron-centered clusters on average displayed stronger functional connectivity between each other than with nonmember pyramidal neurons. The structure of the clusters evolved during postnatal development: cluster size and overlap between clusters decreased with developmental maturation. Pyramidal neurons in a cluster showed higher than chance tuning function similarity between each other and with the linked interneuron. Thus, spontaneous population events in V1 are shaped by small-world subnetworks of pyramidal neurons that share functional properties and work as a coherent unit with a local interneuron. These interneuron-pyramidal cell partnerships may represent a fundamental neocortical unit of computation at the population level.SIGNIFICANCE STATEMENT Neuronal circuit in layer 2/3 of mouse area V1 possesses small-world network architecture, where cliques of densely interconnected neurons ("small worlds") communicate via restricted number of hub cells. We show that: (1) in mouse V1 individual small-world cliques preferably incorporate pyramidal neurons with similar visual feature tuning, and (2) ongoing population activity of such pyramidal neuron clique is temporally linked to the activity of the local interneuron sharing its feature tuning with the clique members. Functional grouping of similarly tuned interneurons and pyramidal cells into cliques may ensure that ensembles of functionally alike pyramidal cells recruited during perceptual tasks and spontaneous activity are also turned off together as a unit, with interneurons serving as organizers of linked pyramidal ensemble activity.

Ferrets as a Model for Higher-Level Visual Motion Processing

Ferrets are a major developmental animal model due to their early parturition. Here we show for the first time that ferrets could be used to study development of higher-level visual processes previously identified in primates. In primates, complex motion processing involves primary visual cortex (V1), which generates local motion signals, and higher-level visual area MT, which integrates these signals over more global spatial regions. Our data show similar transformations in motion signals between ferret V1 and higher-level visual area PSS, located in the posterior bank of the suprasylvian sulcus. We found that PSS neurons, like MT neurons, were tuned for stimulus motion and showed strong suppression between opposing direction inputs. Most strikingly, PSS, like MT, exhibited robust global motion signals when tested with coherent plaids-the classic test for motion integration across multiple moving elements. These PSS responses were described well by computational models developed for MT. Our findings establish the ferret as a strong animal model for development of higher-level visual processing.

Flow stimuli reveal ecologically appropriate responses in mouse visual cortex

Assessments of the mouse visual system based on spatial-frequency analysis imply that its visual capacity is low, with few neurons responding to spatial frequencies greater than 0.5 cycles per degree. However, visually mediated behaviors, such as prey capture, suggest that the mouse visual system is more precise. We introduce a stimulus class-visual flow patterns-that is more like what the mouse would encounter in the natural world than are sine-wave gratings but is more tractable for analysis than are natural images. We used 128-site silicon microelectrodes to measure the simultaneous responses of single neurons in the primary visual cortex (V1) of alert mice. While holding temporal-frequency content fixed, we explored a class of drifting patterns of black or white dots that have energy only at higher spatial frequencies. These flow stimuli evoke strong visually mediated responses well beyond those predicted by spatial-frequency analysis. Flow responses predominate in higher spatial-frequency ranges (0.15-1.6 cycles per degree), many are orientation or direction selective, and flow responses of many neurons depend strongly on sign of contrast. Many cells exhibit distributed responses across our stimulus ensemble. Together, these results challenge conventional linear approaches to visual processing and expand our understanding of the mouse's visual capacity to behaviorally relevant ranges.

Self-motion processing in visual and entorhinal cortices: inputs, integration, and implications for position coding

The sensory signals generated by self-motion are complex and multimodal, but the ability to integrate these signals into a unified self-motion percept to guide navigation is essential for animal survival. Here, we summarize classic and recent work on self-motion coding in the visual and entorhinal cortices of the rodent brain. We compare motion processing in rodent and primate visual cortices, highlighting the strengths of classic primate work in establishing causal links between neural activity and perception, and discuss the integration of motor and visual signals in rodent visual cortex. We then turn to the medial entorhinal cortex (MEC), where calculations using self-motion to update position estimates are thought to occur. We focus on several key sources of self-motion information to MEC: the medial septum, which provides locomotor speed information; visual cortex, whose input has been increasingly recognized as essential to both position and speed-tuned MEC cells; and the head direction system, which is a major source of directional information for self-motion estimates. These inputs create a large and diverse group of self-motion codes in MEC, and great interest remains in how these self-motion codes might be integrated by MEC grid cells to estimate position. However, which signals are used in these calculations and the mechanisms by which they are integrated remain controversial. We end by proposing future experiments that could further our understanding of the interactions between MEC cells that code for self-motion and position and clarify the relationship between the activity of these cells and spatial perception.

A Role for Mouse Primary Visual Cortex in Motion Perception

Visual motion is an ethologically important stimulus throughout the animal kingdom. In primates, motion perception relies on specific higher-order cortical regions. Although mouse primary visual cortex (V1) and higher-order visual areas show direction-selective (DS) responses, their role in motion perception remains unknown. Here, we tested whether V1 is involved in motion perception in mice. We developed a head-fixed discrimination task in which mice must report their perceived direction of motion from random dot kinematograms (RDKs). After training, mice made around 90% correct choices for stimuli with high coherence and performed significantly above chance for 16% coherent RDKs. Accuracy increased with both stimulus duration and visual field coverage of the stimulus, suggesting that mice in this task integrate motion information in time and space. Retinal recordings showed that thalamically projecting On-Off DS ganglion cells display DS responses when stimulated with RDKs. Two-photon calcium imaging revealed that neurons in layer (L) 2/3 of V1 display strong DS tuning in response to this stimulus. Thus, RDKs engage motion-sensitive retinal circuits as well as downstream visual cortical areas. Contralateral V1 activity played a key role in this motion direction discrimination task because its reversible inactivation with muscimol led to a significant reduction in performance. Neurometric-psychometric comparisons showed that an ideal observer could solve the task with the information encoded in DS L2/3 neurons. Motion discrimination of RDKs presents a powerful behavioral tool for dissecting the role of retino-forebrain circuits in motion processing.

Coding of self-motion-induced and self-independent visual motion in the rat dorsomedial striatum

Evolutionary development of vision has provided us with the capacity to detect moving objects. Concordant shifts of visual features suggest movements of the observer, whereas discordant changes are more likely to be indicating independently moving objects, such as predators or prey. Such distinction helps us to focus attention, adapt our behavior, and adjust our motor patterns to meet behavioral challenges. However, the neural basis of distinguishing self-induced and self-independent visual motions is not clarified in unrestrained animals yet. In this study, we investigated the presence and origin of motion-related visual information in the striatum of rats, a hub of action selection and procedural memory. We found that while almost half of the neurons in the dorsomedial striatum are sensitive to visual motion congruent with locomotion (and that many of them also code for spatial location), only a small subset of them are composed of fast-firing interneurons that could also perceive self-independent visual stimuli. These latter cells receive their visual input at least partially from the secondary visual cortex (V2). This differential visual sensitivity may be an important support in adjusting behavior to salient environmental events. It emphasizes the importance of investigating visual motion perception in unrestrained animals.

A micro-CT-based method for quantitative brain lesion characterization and electrode localization

Lesion verification and quantification is traditionally done via histological examination of sectioned brains, a time-consuming process that relies heavily on manual estimation. Such methods are particularly problematic in posterior cortical regions (e.g. visual cortex), where sectioning leads to significant damage and distortion of tissue. Even more challenging is the post hoc localization of micro-electrodes, which relies on the same techniques, suffers from similar drawbacks and requires even higher precision. Here, we propose a new, simple method for quantitative lesion characterization and electrode localization that is less labor-intensive and yields more detailed results than conventional methods. We leverage staining techniques standard in electron microscopy with the use of commodity micro-CT imaging. We stain whole rat and zebra finch brains in osmium tetroxide, embed these in resin and scan entire brains in a micro-CT machine. The scans result in 3D reconstructions of the brains with section thickness dependent on sample size (12-15 and 5-6 microns for rat and zebra finch respectively) that can be segmented manually or automatically. Because the method captures the entire intact brain volume, comparisons within and across studies are more tractable, and the extent of lesions and electrodes may be studied with higher accuracy than with current methods.

Circuit Mechanisms Governing Local vs. Global Motion Processing in Mouse Visual Cortex

A withstanding question in neuroscience is how neural circuits encode representations and perceptions of the external world. A particularly well-defined visual computation is the representation of global object motion by pattern direction-selective (PDS) cells from convergence of motion of local components represented by component direction-selective (CDS) cells. However, how PDS and CDS cells develop their distinct response properties is still unresolved. The visual cortex of the mouse is an attractive model for experimentally solving this issue due to the large molecular and genetic toolbox available. Although mouse visual cortex lacks the highly ordered orientation columns of primates, it is organized in functional sub-networks and contains striate- and extrastriate areas like its primate counterparts. In this Perspective article, we provide an overview of the experimental and theoretical literature on global motion processing based on works in primates and mice. Lastly, we propose what types of experiments could illuminate what circuit mechanisms are governing cortical global visual motion processing. We propose that PDS cells in mouse visual cortex appear as the perfect arena for delineating and solving how individual sensory features extracted by neural circuits in peripheral brain areas are integrated to build our rich cohesive sensory experiences.

Specific excitatory connectivity for feature integration in mouse primary visual cortex

Local excitatory connections in mouse primary visual cortex (V1) are stronger and more prevalent between neurons that share similar functional response features. However, the details of how functional rules for local connectivity shape neuronal responses in V1 remain unknown. We hypothesised that complex responses to visual stimuli may arise as a consequence of rules for selective excitatory connectivity within the local network in the superficial layers of mouse V1. In mouse V1 many neurons respond to overlapping grating stimuli (plaid stimuli) with highly selective and facilitatory responses, which are not simply predicted by responses to single gratings presented alone. This complexity is surprising, since excitatory neurons in V1 are considered to be mainly tuned to single preferred orientations. Here we examined the consequences for visual processing of two alternative connectivity schemes: in the first case, local connections are aligned with visual properties inherited from feedforward input (a 'like-to-like' scheme specifically connecting neurons that share similar preferred orientations); in the second case, local connections group neurons into excitatory subnetworks that combine and amplify multiple feedforward visual properties (a 'feature binding' scheme). By comparing predictions from large scale computational models with in vivo recordings of visual representations in mouse V1, we found that responses to plaid stimuli were best explained by assuming feature binding connectivity. Unlike under the like-to-like scheme, selective amplification within feature-binding excitatory subnetworks replicated experimentally observed facilitatory responses to plaid stimuli; explained selective plaid responses not predicted by grating selectivity; and was consistent with broad anatomical selectivity observed in mouse V1. Our results show that visual feature binding can occur through local recurrent mechanisms without requiring feedforward convergence, and that such a mechanism is consistent with visual responses and cortical anatomy in mouse V1.

Dictionary Learning for Spontaneous Neural Activity Modeling

Modeling the activity of an ensemble of neurons can provide critical insights into the workings of the brain. In this work we examine if learning based signal modeling can contribute to a high quality modeling of neuronal signal data. To that end, we employ the sparse coding and dictionary learning schemes for capturing the behavior of neuronal responses into a small number of representative prototypical signals. Performance is measured by the reconstruction quality of clean and noisy test signals, which serves as an indicator of the generalization and discrimination capabilities of the learned dictionaries. To validate the merits of the proposed approach, a novel dataset of the actual recordings from 183 neurons from the primary visual cortex of a mouse in early postnatal development was developed and investigated. The results demonstrate that high quality modeling of testing data can be achieved from a small number of training examples and that the learned dictionaries exhibit significant specificity when introducing noise.