Unique Spatial Integration in Mouse Primary Visual Cortex and Higher Visual Areas.

Neurons in the visual system integrate over a wide range of spatial scales. This diversity is thought to enable both local and global computations. To understand how spatial information is encoded across the mouse visual system, we use two-photon imaging to measure receptive fields (RFs) and size-tuning in primary visual cortex (V1) and three downstream higher visual areas (HVAs: LM (lateromedial), AL (anterolateral), and PM (posteromedial)) in mice of both sexes. Neurons in PM, compared with V1 or the other HVAs, have significantly larger RF sizes and less surround suppression, independent of stimulus eccentricity or contrast. To understand how this specialization of RFs arises in the HVAs, we measured the spatial properties of V1 inputs to each area. Spatial integration of V1 axons was remarkably similar across areas and significantly different from the tuning of neurons in their target HVAs. Thus, unlike other visual features studied in this system, specialization of spatial integration in PM cannot be explained by specific projections from V1 to the HVAs. Further, the differences in RF properties could not be explained by differences in convergence of V1 inputs to the HVAs. Instead, our data suggest that distinct inputs from other areas or connectivity within PM may support the area's unique ability to encode global features of the visual scene, whereas V1, LM, and AL may be more specialized for processing local features.SIGNIFICANCE STATEMENT Surround suppression is a common feature of visual processing whereby large stimuli are less effective at driving neuronal responses than smaller stimuli. This is thought to enhance efficiency in the population code and enable higher-order processing of visual information, such as figure-ground segregation. However, this comes at the expense of global computations. Here we find that surround suppression is not equally represented across mouse visual areas: primary visual cortex has substantially more surround suppression than higher visual areas, and one higher area has significantly less suppression than two others examined, suggesting that these areas have distinct functional roles. Thus, we have identified a novel dimension of specialization in the mouse visual cortex that may enable both local and global computations.

Disparity Sensitivity and Binocular Integration in Mouse Visual Cortex Areas.

Binocular disparity, the difference between the two eyes' images, is a powerful cue to generate the 3D depth percept known as stereopsis. In primates, binocular disparity is processed in multiple areas of the visual cortex, with distinct contributions of higher areas to specific aspects of depth perception. Mice, too, can perceive stereoscopic depth, and neurons in primary visual cortex (V1) and higher-order, lateromedial (LM) and rostrolateral (RL) areas were found to be sensitive to binocular disparity. A detailed characterization of disparity tuning across mouse visual areas is lacking, however, and acquiring such data might help clarifying the role of higher areas for disparity processing and establishing putative functional correspondences to primate areas. We used two-photon calcium imaging in female mice to characterize the disparity tuning properties of neurons in visual areas V1, LM, and RL in response to dichoptically presented binocular gratings, as well as random dot correlograms (RDC). In all three areas, many neurons were tuned to disparity, showing strong response facilitation or suppression at optimal or null disparity, respectively, even in neurons classified as monocular by conventional ocular dominance (OD) measurements. Neurons in higher areas exhibited broader and more asymmetric disparity tuning curves compared with V1, as observed in primate visual cortex. Finally, we probed neurons' sensitivity to true stereo correspondence by comparing responses to correlated RDC (cRDC) and anticorrelated RDC (aRDC). Area LM, akin to primate ventral visual stream areas, showed higher selectivity for correlated stimuli and reduced anticorrelated responses, indicating higher-level disparity processing in LM compared with V1 and RL.SIGNIFICANCE STATEMENT A major cue for inferring 3D depth is disparity between the two eyes' images. Investigating how binocular disparity is processed in the mouse visual system will not only help delineating the role of mouse higher areas for visual processing, but also shed light on how the mammalian brain computes stereopsis. We found that binocular integration is a prominent feature of mouse visual cortex, as many neurons are selectively and strongly modulated by binocular disparity. Comparison of responses to correlated and anticorrelated random dot correlograms (RDC) revealed that lateromedial area (LM) is more selective to correlated stimuli, while less sensitive to anticorrelated stimuli compared with primary visual cortex (V1) and rostrolateral area (RL), suggesting higher-level disparity processing in LM, resembling primate ventral visual stream areas.

Contribution of Sensory Encoding to Measured Bias.

Signal detection theory (SDT) is a widely used theoretical framework that describes how variable sensory signals are integrated with a decision criterion to support perceptual decision-making. SDT provides two key measurements: sensitivity (d') and bias (c), which reflect the separability of decision variable distributions (signal and noise) and the position of the decision criterion relative to optimal, respectively. Although changes in the subject's decision criterion can be reflected in changes in bias, decision criterion placement is not the sole contributor to measured bias. Indeed, neuronal representations of bias have been observed in sensory areas, suggesting that some changes in bias are because of effects on sensory encoding. To directly test whether the sensory encoding process can influence bias, we optogenetically manipulated neuronal excitability in primary visual cortex (V1) in mice of both sexes during either an orientation discrimination or a contrast detection task. Increasing excitability in V1 significantly decreased behavioral bias, whereas decreasing excitability had the opposite effect. To determine whether this change in bias is consistent with effects on sensory encoding, we made extracellular recordings from V1 neurons in passively viewing mice. Indeed, we found that optogenetic manipulation of excitability shifted the neuronal bias in the same direction as the behavioral bias. Moreover, manipulating the quality of V1 encoding by changing stimulus contrast or interstimulus interval also resulted in consistent changes in both behavioral and neuronal bias. Thus, changes in sensory encoding are sufficient to drive changes in bias measured using SDT.SIGNIFICANCE STATEMENT Perceptual decision-making involves sensory integration followed by application of a cognitive criterion. Using signal detection theory, one can extract features of the underlying decision variables and rule: sensitivity (d') and bias (c). Because bias is measured as the difference between the optimal and actual criterion, it is sensitive to both the sensory encoding processes and the placement of the decision criterion. Here, we use behavioral and electrophysiological approaches to demonstrate that measures of bias depend on sensory processes. Optogenetic manipulations of V1 in mice bidirectionally affect both behavioral and neuronal measures of bias with little effect on sensitivity. Thus, changes in sensory encoding influence bias, and the absence of changes in sensitivity do not preclude changes in sensory encoding.

In Vivo Submillisecond Two-Photon Optogenetics with Temporally Focused Patterned Light.

To better examine circuit mechanisms underlying perception and behavior, researchers need tools to enable temporally precise control of action-potential generation of individual cells from neuronal ensembles. Here we demonstrate that such precision can be achieved with two-photon (2P) temporally focused computer-generated holography to control neuronal excitability at the supragranular layers of anesthetized and awake visual cortex in both male and female mice. Using 2P-guided whole-cell or cell-attached recordings in positive neurons expressing any of the three opsins ReaChR, CoChR, or ChrimsonR, we investigated the dependence of spiking activity on the opsin's channel kinetics. We found that in all cases the use of brief illumination (≤10 ms) induces spikes of millisecond temporal resolution and submillisecond precision, which were preserved upon repetitive illuminations up to tens of hertz. To reach high temporal precision, we used a large illumination spot covering the entire cell body and an amplified laser at high peak power and low excitation intensity (on average ≤0.2 mW/µm2), thus minimizing the risk for nonlinear photodamage effects. Finally, by combining 2P holographic excitation with electrophysiological recordings and calcium imaging using GCaMP6s, we investigated the factors, including illumination shape and intensity, opsin distribution in the target cell, and cell morphology, which affect the spatial selectivity of single-cell and multicell holographic activation. Parallel optical control of neuronal activity with cellular resolution and millisecond temporal precision should make it easier to investigate neuronal connections and find further links between connectivity, microcircuit dynamics, and brain functions.SIGNIFICANCE STATEMENT Recent developments in the field of optogenetics has enabled researchers to probe the neuronal microcircuit with light by optically actuating genetically encoded light-sensitive opsins expressed in the target cells. Here, we applied holographic light shaping and temporal focusing to simultaneously deliver axially confined holographic patterns to opsin-positive cells in the living mouse cortex. Parallel illumination efficiently induced action potentials with high temporal resolution and precision for three opsins of different kinetics. We extended the parallel optogenetic activation at low intensity to multiple neurons and concurrently monitored their calcium dynamics. These results demonstrate fast and temporally precise in vivo control of a neuronal subpopulation, opening new opportunities for revealing circuit mechanisms underlying brain functions.

Internal Gain Modulations, But Not Changes in Stimulus Contrast, Preserve the Neural Code.

Neurons in primary visual cortex are strongly modulated both by stimulus contrast and by fluctuations of internal inputs. An important question is whether the population code is preserved under these conditions. Changes in stimulus contrast are thought to leave the population code invariant, whereas the effect of internal gain modulations remains unknown. To address these questions we studied how the direction-of-motion of oriented gratings is encoded in layer 2/3 primary visual cortex of mouse (with C57BL/6 background, of either sex). We found that, because contrast gain responses across cells are heterogeneous, a change in contrast alters the information distribution profile across cells leading to a violation of contrast invariance. Remarkably, internal input fluctuations that cause commensurate firing rate modulations at the single-cell level result in more homogeneous gain responses, respecting population code invariance. These observations argue that the brain strives to maintain the stability of the neural code in the face of fluctuating internal inputs.SIGNIFICANCE STATEMENT Neuronal responses are modulated both by stimulus contrast and by the spontaneous fluctuation of internal inputs. It is not well understood how these different types of input impact the population code. Specifically, it is important to understand whether the neural code stays invariant in the face of significant internal input modulations. Here, we show that changes in stimulus contrast lead to different optimal population codes, whereas spontaneous internal input fluctuations leave the population code invariant. This is because spontaneous internal input fluctuations modulate the gain of neuronal responses more homogeneously across cells compared to changes in stimulus contrast.

Binocular Disparity Selectivity Weakened after Monocular Deprivation in Mouse V1.

Experiences during the critical period sculpt the circuitry within the neocortex, leading to changes in the functional responses of sensory neurons. Monocular deprivation (MD) during the visual critical period causes shifts in ocular preference, or dominance, toward the open eye in primary visual cortex (V1) and disrupts the normal development of acuity. In carnivores and primates, MD also disrupts the emergence of binocular disparity selectivity, a cue resulting from integrating ocular inputs. This disruption may be a result of the increase in neurons driven exclusively by the open eye that follows deprivation or a result of a mismatch in the convergence of ocular inputs. To distinguish between these possibilities, we measured the ocular dominance (OD) and disparity selectivity of neurons from male and female mouse V1 following MD. Normal mouse V1 neurons are dominated by contralateral eye input and contralateral eye deprivation shifts mouse V1 neurons toward more balanced responses between the eyes. This shift toward binocularity, as assayed by OD, decreased disparity sensitivity. MD did not alter the initial maturation of binocularity, as disparity selectivity before the MD was indistinguishable from normal mature animals. Decreased disparity tuning was most pronounced in binocular and ipsilaterally biased neurons, which are the populations that have undergone the largest shifts in OD. In concert with the decline in disparity selectivity, we observed a shift toward lower spatial frequency selectivity for the ipsilateral eye following MD. These results suggest an emergence of novel synaptic inputs during MD that disrupt the representation of disparity selectivity.SIGNIFICANCE STATEMENT We demonstrate that monocular deprivation during the developmental critical period impairs binocular integration in mouse primary visual cortex. This impairment occurs despite an increase in the degree to which neurons become more binocular. We further demonstrate that our deprivation did not impair the maturation of disparity selectivity. Disparity selectivity has already reached a matured level before the monocular deprivation. The loss of disparity tuning is primarily observed in neurons dominated by the open eye, suggesting a link between altered inputs and loss of disparity sensitivity. These results suggest that new inputs following deprivation may not maintain the precise spatial relationship between the two eye inputs required for disparity selectivity.

Functional Segregation and Development of Mouse Higher Visual Areas.

Recent studies suggest that higher visual areas (HVAs) in the mouse visual cortex are segregated anatomically into two visual streams, likely analogous to the ventral and dorsal streams in primates. However, HVAs in mice have yet to be characterized functionally. Moreover, it is unknown when the functional segregation of HVAs occurs during development. Here, we investigated spatiotemporal selectivity of HVAs and their development using wide-field calcium imaging. We found that lateral HVAs in the anatomical ventral stream shared similar spatiotemporal selectivity, whereas the spatiotemporal selectivity of anterior and medial HVAs in the anatomical dorsal stream was not uniform and these areas were segregated functionally into multiple groups. This functional segregation of HVAs developed and reached an adult-like pattern ∼10 d after eye opening (EO). These results suggest, not only the functional segregation of ventral and dorsal streams, but also the presence of multiple substreams in the dorsal stream, and indicate that the functional segregation of visual streams occurs gradually after EO.SIGNIFICANCE STATEMENT Investigation of the spatiotemporal selectivity of nine higher visual areas (HVAs) in adult and developing mice revealed that lateral HVAs belonging to the putative ventral stream shared similar spatiotemporal selectivity, whereas the spatiotemporal selectivity of anterior and medial HVAs belonging to the putative dorsal stream was not uniform and these areas were segregated functionally into multiple groups. These results suggest the presence of multiple substreams within the putative dorsal stream for visuospatial processing. Furthermore, we found that initially immature functional segregation among HVAs developed to an adult-like pattern ∼10 d after eye opening. These results provide a foundation for using mouse HVAs as a model to understand parallel processing and its developmental mechanism.

Orientation-tuned surround suppression in mouse visual cortex.

The firing rates of neurons in primary visual cortex (V1) are suppressed by large stimuli, an effect known as surround suppression. In cats and monkeys, the strength of suppression is sensitive to orientation; responses to regions containing uniform orientations are more suppressed than those containing orientation contrast. This effect is thought to be important for scene segmentation, but the underlying neural mechanisms are poorly understood. We asked whether it is possible to study these mechanisms in the visual cortex of mice, because of recent advances in technology for studying the cortical circuitry in mice. It is unknown whether neurons in mouse V1 are sensitive to orientation contrast. We measured the orientation selectivity of surround suppression in the different layers of mouse V1. We found strong surround suppression in layer 4 and the superficial layers, part of which was orientation tuned: iso-oriented surrounds caused more suppression than cross-oriented surrounds. Surround suppression was delayed relative to the visual response and orientation-tuned suppression was delayed further, suggesting two separate suppressive mechanisms. Previous studies proposed that surround suppression depends on the activity of inhibitory somatostatin-positive interneurons in the superficial layers. To test the involvement of the superficial layers we topically applied lidocaine. Silencing of the superficial layers did not prevent orientation-tuned suppression in layer 4. These results show that neurons in mouse V1, which lacks orientation columns, show orientation-dependent surround suppression in layer 4 and the superficial layers and that surround suppression in layer 4 does not require contributions from neurons in the superficial layers.

Emergence of feature-specific connectivity in cortical microcircuits in the absence of visual experience.

In primary visual cortex (V1), connectivity between layer 2/3 (L2/3) excitatory neurons undergoes extensive reorganization after the onset of visual experience whereby neurons with similar feature selectivity form functional microcircuits (Ko et al., 2011, 2013). It remains unknown whether visual experience is required for the developmental refinement of intracortical circuitry or whether this maturation is guided intrinsically. Here, we correlated the connectivity between V1 L2/3 neurons assayed by simultaneous whole-cell recordings in vitro to their response properties measured by two-photon calcium imaging in vivo in dark-reared mice. We found that neurons with similar responses to oriented gratings or natural movies became preferentially connected in the absence of visual experience. However, the relationship between connectivity and similarity of visual responses to natural movies was not as strong in dark-reared as in normally reared mice. Moreover, dark rearing prevented the normally occurring loss of connections between visually nonresponsive neurons after eye opening (Ko et al., 2013). Therefore, our data suggest that the absence of visual input does not prevent the emergence of functionally specific recurrent connectivity in cortical circuits; however, visual experience is required for complete microcircuit maturation.

Mouse primary visual cortex is used to detect both orientation and contrast changes.

In mammals, the lateral geniculate nucleus (LGN) and the superior colliculus (SC) are the major targets of visual inputs from the retina. The LGN projects mainly to primary visual cortex (V1) while the SC targets the thalamus and brainstem, providing two potential pathways for processing visual inputs. Indeed, cortical lesion experiments in rodents have yielded mixed results, leading to the hypothesis that performance of simple visual behaviors may involve computations performed entirely by this subcortical pathway through the SC. However, these previous experiments have been limited by both their assays of behavioral performance and their use of lesions to change cortical activity. To determine the contribution of V1 to these tasks, we trained mice to perform threshold detection tasks in which they reported changes in either the contrast or orientation of visual stimuli. We then reversibly inhibited V1 by optogenetically activating parvalbumin-expressing inhibitory neurons with channelrhodopsin-2. We found that suppressing activity in V1 substantially impaired performance in visual detection tasks. The behavioral deficit depended on the retinotopic position of the visual stimulus, confirming that the effect was due to the specific suppression of the visually driven V1 neurons. Behavioral effects were seen with only moderate changes in neuronal activity, as inactivation that raised neuronal contrast thresholds by a median of only 14% was associated with a doubling of behavioral contrast detection threshold. Thus, detection of changes in either orientation or contrast is dependent on, and highly sensitive to, the activity of neurons in V1.

Cholinergic input to mouse visual cortex signals a movement state and acutely enhances layer 5 responsiveness.

Acetylcholine is released in visual cortex by axonal projections from the basal forebrain. The signals conveyed by these projections and their computational significance are still unclear. Using two-photon calcium imaging in behaving mice, we show that basal forebrain cholinergic axons in the mouse visual cortex provide a binary locomotion state signal. In these axons, we found no evidence of responses to visual stimuli or visuomotor prediction errors. While optogenetic activation of cholinergic axons in visual cortex in isolation did not drive local neuronal activity, when paired with visuomotor stimuli, it resulted in layer-specific increases of neuronal activity. Responses in layer 5 neurons to both top-down and bottom-up inputs were increased in amplitude and decreased in latency, whereas those in layer 2/3 neurons remained unchanged. Using opto- and chemogenetic manipulations of cholinergic activity, we found acetylcholine to underlie the locomotion-associated decorrelation of activity between neurons in both layer 2/3 and layer 5. Our results suggest that acetylcholine augments the responsiveness of layer 5 neurons to inputs from outside of the local network, possibly enabling faster switching between internal representations during locomotion.

Saccade-Responsive Visual Cortical Neurons Do Not Exhibit Distinct Visual Response Properties.

Rapid saccadic eye movements are used by animals to sample different parts of the visual scene. Previous work has investigated neural correlates of these saccades in visual cortical areas such as V1; however, how saccade-responsive neurons are distributed across visual areas, cell types, and cortical layers has remained unknown. Through analyzing 818 1 h experimental sessions from the Allen Brain Observatory, we present a large-scale analysis of saccadic behaviors in head-fixed mice and their neural correlates. We find that saccade-responsive neurons are present across visual cortex, but their distribution varies considerably by transgenically defined cell type, cortical area, and cortical layer. We also find that saccade-responsive neurons do not exhibit distinct visual response properties from the broader neural population, suggesting that the saccadic responses of these neurons are likely not predominantly visually driven. These results provide insight into the roles played by different cell types within a broader, distributed network of sensory and motor interactions.

The Dynamic Sensorium competition for predicting large-scale mouse visual cortex activity from videos.

Understanding how biological visual systems process information is challenging due to the complex nonlinear relationship between neuronal responses and high-dimensional visual input. Artificial neural networks have already improved our understanding of this system by allowing computational neuroscientists to create predictive models and bridge biological and machine vision. During the Sensorium 2022 competition, we introduced benchmarks for vision models with static input (i.e. images). However, animals operate and excel in dynamic environments, making it crucial to study and understand how the brain functions under these conditions. Moreover, many biological theories, such as predictive coding, suggest that previous input is crucial for current input processing. Currently, there is no standardized benchmark to identify state-of-the-art dynamic models of the mouse visual system. To address this gap, we propose the Sensorium 2023 Benchmark Competition with dynamic input (https://www.sensorium-competition.net/). This competition includes the collection of a new large-scale dataset from the primary visual cortex of five mice, containing responses from over 38,000 neurons to over 2 hours of dynamic stimuli per neuron. Participants in the main benchmark track will compete to identify the best predictive models of neuronal responses for dynamic input (i.e. video). We will also host a bonus track in which submission performance will be evaluated on out-of-domain input, using withheld neuronal responses to dynamic input stimuli whose statistics differ from the training set. Both tracks will offer behavioral data along with video stimuli. As before, we will provide code, tutorials, and strong pre-trained baseline models to encourage participation. We hope this competition will continue to strengthen the accompanying Sensorium benchmarks collection as a standard tool to measure progress in large-scale neural system identification models of the entire mouse visual hierarchy and beyond.

Narrowband gamma oscillations propagate and synchronize throughout the mouse thalamocortical visual system.

Oscillations of neural activity permeate sensory systems. In the visual system, broadband gamma oscillations (30-80 Hz) are thought to act as a communication mechanism underlying perception. However, these oscillations show widely varying frequency and phase, providing constraints for coordinating spike timing across areas. Here, we examined Allen Brain Observatory data and performed causal experiments to show that narrowband gamma (NBG) oscillations (50-70 Hz) propagate and synchronize throughout the awake mouse visual system. Lateral geniculate nucleus (LGN) neurons fired precisely relative to NBG phase in primary visual cortex (V1) and multiple higher visual areas (HVAs). NBG neurons across areas showed a higher likelihood of functional connectivity and stronger visual responses; remarkably, NBG neurons in LGN, preferring bright (ON) versus dark (OFF), fired at distinct NBG phases aligned across the cortical hierarchy. NBG oscillations may thus serve to coordinate spike timing across brain areas and facilitate communication of distinct visual features during perception.

Computational assessment of visual coding across mouse brain areas and behavioural states.

Introduction: Our brain is bombarded by a diverse range of visual stimuli, which are converted into corresponding neuronal responses and processed throughout the visual system. The neural activity patterns that result from these external stimuli vary depending on the object or scene being observed, but they also change as a result of internal or behavioural states. This raises the question of to what extent it is possible to predict the presented visual stimuli from neural activity across behavioural states, and how this varies in different brain regions. Methods: To address this question, we assessed the computational capacity of decoders to extract visual information in awake behaving mice, by analysing publicly available standardised datasets from the Allen Brain Institute. We evaluated how natural movie frames can be distinguished based on the activity of units recorded in distinct brain regions and under different behavioural states. This analysis revealed the spectrum of visual information present in different brain regions in response to binary and multiclass classification tasks. Results: Visual cortical areas showed highest classification accuracies, followed by thalamic and midbrain regions, with hippocampal regions showing close to chance accuracy. In addition, we found that behavioural variability led to a decrease in decoding accuracy, whereby large behavioural changes between train and test sessions reduced the classification performance of the decoders. A generalised linear model analysis suggested that this deterioration in classification might be due to an independent modulation of neural activity by stimulus and behaviour. Finally, we reconstructed the natural movie frames from optimal linear classifiers, and observed a strong similarity between reconstructed and actual movie frames. However, the similarity was significantly higher when the decoders were trained and tested on sessions with similar behavioural states. Conclusion: Our analysis provides a systematic assessment of visual coding in the mouse brain, and sheds light on the spectrum of visual information present across brain areas and behavioural states.

SynapseCLR: Uncovering features of synapses in primary visual cortex through contrastive representation learning.

3D electron microscopy (EM) connectomics image volumes are surpassing 1 mm3, providing information-dense, multi-scale visualizations of brain circuitry and necessitating scalable analysis techniques. We present SynapseCLR, a self-supervised contrastive learning method for 3D EM data, and use it to extract features of synapses from mouse visual cortex. SynapseCLR feature representations separate synapses by appearance and functionally important structural annotations. We demonstrate SynapseCLR's utility for valuable downstream tasks, including one-shot identification of defective synapse segmentations, dataset-wide similarity-based querying, and accurate imputation of annotations for unlabeled synapses, using manual annotation of only 0.2% of the dataset's synapses. In particular, excitatory versus inhibitory neuronal types can be assigned with >99.8% accuracy to individual synapses and highly truncated neurites, enabling neurite-enhanced connectomics analysis. Finally, we present a data-driven, unsupervised study of synaptic structural variation on the representation manifold, revealing its intrinsic axes of variation and showing that representations contain inhibitory subtype information.

Visual cortex encodes timing information in humans and mice.

Despite the importance of timing in our daily lives, our understanding of how the human brain mediates second-scale time perception is limited. Here, we combined intracranial stereoelectroencephalography (SEEG) recordings in epileptic patients and circuit dissection in mice to show that visual cortex (VC) encodes timing information. We first asked human participants to perform an interval-timing task and found VC to be a key timing brain area. We then conducted optogenetic experiments in mice and showed that VC plays an important role in the interval-timing behavior. We further found that VC neurons fired in a time-keeping sequential manner and exhibited increased excitability in a timed manner. Finally, we used a computational model to illustrate a self-correcting learning process that generates interval-timed activities with scalar-timing property. Our work reveals how localized oscillations in VC occurring in the seconds to deca-seconds range relate timing information from the external world to guide behavior.

Monosynaptic rabies virus tracing from projection-targeted single neurons.

A single neuron integrates inputs from thousands of presynaptic neurons to generate outputs. Circuit tracing using G-deleted rabies virus (RVΔG) vectors permits the brain-wide labeling of presynaptic inputs to targeted single neurons. However, the experimental procedures are complex, and the success rate of circuit labeling is low because of the lack of validation to increase the accuracy and efficiency of monosynaptic RVΔG tracing from targeted single neurons. We established an efficient RVΔG tracing method from projection target-defined single neurons using TVA950, a transmembrane isoform of TVA receptors, for initial viral infection. Presynaptic neurons were transsynaptically labeled from 80 % of the TVA950-expressing single starter neurons that survived after infection with EnvA-pseudotyped RVΔG in the adult mouse brain. We labeled single neuronal networks in the primary visual cortex (V1) and higher visual areas, namely the posteromedial area (PM) and anteromedial area (AM), as well as the single neuronal networks of PM-projecting V1 single neurons. Monosynaptic RVΔG tracing from projection-targeted single neurons revealed the input-output organization of single neuronal networks. Single-neuron network analysis based on RVΔG tracing will help dissect the heterogeneity of neural circuits and link circuit motifs and large-scale networks across scales, thereby clarifying information processing and circuit computation in the brain.

Motion Streak Neurons in the Mouse Visual Cortex.

Motion streaks are smeared representation of fast-moving objects due to temporal integration. Here, we test for motion streak signals in mice with two-photon calcium imaging. For small dots moving at low speeds, neurons in primary visual cortex (V1) encode the component motion, with preferred direction along the axis perpendicular to their preferred orientation. At high speeds, V1 neurons prefer the direction along the axis parallel to their preferred orientation, as expected for encoding motion streaks. Whereas some V1 neurons (∼20%) display a switch of preferred motion axis with increasing speed, others (>40%) respond specifically to high speeds at the parallel axis. Motion streak neurons are also seen in higher visual lateromedial (LM), anterolateral (AL), and rostrolateral (RL) areas, but with higher transition speeds, and many still prefer the perpendicular axis even with fast motion. Our results thus indicate that diverse motion encoding exists in mouse visual cortex, with intriguing differences among visual areas.

A systematic topographical relationship between mouse lateral posterior thalamic neurons and their visual cortical projection targets.

Higher-order visual thalamus communicates broadly and bi-directionally with primary and extrastriate cortical areas in various mammals. In primates, the pulvinar is a topographically and functionally organized thalamic nucleus that is largely dedicated to visual processing. Still, a more granular connectivity map is needed to understand the role of thalamocortical loops in visually guided behavior. Similarly, the secondary visual thalamic nucleus in mice (the lateral posterior nucleus, LP) has extensive connections with cortex. To resolve the precise connectivity of these circuits, we first mapped mouse visual cortical areas using intrinsic signal optical imaging and then injected fluorescently tagged retrograde tracers (cholera toxin subunit B) into retinotopically-matched locations in various combinations of seven different visual areas. We find that LP neurons representing matched regions in visual space but projecting to different extrastriate areas are found in different topographically organized zones, with few double-labeled cells (~4-6%). In addition, V1 and extrastriate visual areas received input from the ventrolateral part of the laterodorsal nucleus of the thalamus (LDVL). These observations indicate that the thalamus provides topographically organized circuits to each mouse visual area and raise new questions about the contributions from LP and LDVL to cortical activity.