A primary sensory cortical interareal feedforward inhibitory circuit for tacto-visual integration.

Tactile sensation and vision are often both utilized for the exploration of objects that are within reach though it is not known whether or how these two distinct sensory systems combine such information. Here in mice, we used a combination of stereo photogrammetry for 3D reconstruction of the whisker array, brain-wide anatomical tracing and functional connectivity analysis to explore the possibility of tacto-visual convergence in sensory space and within the circuitry of the primary visual cortex (VISp). Strikingly, we find that stimulation of the contralateral whisker array suppresses visually evoked activity in a tacto-visual sub-region of VISp whose visual space representation closely overlaps with the whisker search space. This suppression is mediated by local fast-spiking interneurons that receive a direct cortico-cortical input predominantly from layer 6 neurons located in the posterior primary somatosensory barrel cortex (SSp-bfd). These data demonstrate functional convergence within and between two primary sensory cortical areas for multisensory object detection and recognition.

Cortical Integration of Vestibular and Visual Cues for Navigation, Visual Processing, and Perception.

Despite increasing evidence of its involvement in several key functions of the cerebral cortex, the vestibular sense rarely enters our consciousness. Indeed, the extent to which these internal signals are incorporated within cortical sensory representation and how they might be relied upon for sensory-driven decision-making, during, for example, spatial navigation, is yet to be understood. Recent novel experimental approaches in rodents have probed both the physiological and behavioral significance of vestibular signals and indicate that their widespread integration with vision improves both the cortical representation and perceptual accuracy of self-motion and orientation. Here, we summarize these recent findings with a focus on cortical circuits involved in visual perception and spatial navigation and highlight the major remaining knowledge gaps. We suggest that vestibulo-visual integration reflects a process of constant updating regarding the status of self-motion, and access to such information by the cortex is used for sensory perception and predictions that may be implemented for rapid, navigation-related decision-making.

A cortico-collicular circuit for orienting to shelter during escape.

When faced with predatory threats, escape towards shelter is an adaptive action that offers long-term protection against the attacker. Animals rely on knowledge of safe locations in the environment to instinctively execute rapid shelter-directed escape actions1,2. Although previous work has identified neural mechanisms of escape initiation3,4, it is not known how the escape circuit incorporates spatial information to execute rapid flights along the most efficient route to shelter. Here we show that the mouse retrosplenial cortex (RSP) and superior colliculus (SC) form a circuit that encodes the shelter-direction vector and is specifically required for accurately orienting to shelter during escape. Shelter direction is encoded in RSP and SC neurons in egocentric coordinates and SC shelter-direction tuning depends on RSP activity. Inactivation of the RSP-SC pathway disrupts the orientation to shelter and causes escapes away from the optimal shelter-directed route, but does not lead to generic deficits in orientation or spatial navigation. We find that the RSP and SC are monosynaptically connected and form a feedforward lateral inhibition microcircuit that strongly drives the inhibitory collicular network because of higher RSP input convergence and synaptic integration efficiency in inhibitory SC neurons. This results in broad shelter-direction tuning in inhibitory SC neurons and sharply tuned excitatory SC neurons. These findings are recapitulated by a biologically constrained spiking network model in which RSP input to the local SC recurrent ring architecture generates a circular shelter-direction map. We propose that this RSP-SC circuit might be specialized for generating collicular representations of memorized spatial goals that are readily accessible to the motor system during escape, or more broadly, during navigation when the goal must be reached as fast as possible.

Dissecting cellular diversity of cortical GABAergic cells across multiple modalities: A turning point in neuronal taxonomy.

Decoding the complexity of the brain requires an understanding of the architecture, function, and development of its neuronal circuits. Neuronal classifications that group neurons based on specific features/behaviors have become essential to further analyze the different subtypes in a systematic and reproducible way. A comprehensive taxonomic framework, accounting for multiple defining and quantitative features, will provide the reference to infer generalized rules for cells ascribed to the same neuronal type, and eventually predict cellular behaviors, even in the absence of experimental measures. Technologies that enable cell-type classification in the nervous system are rapidly evolving in scalability and resolution. While these approaches depict astonishing diversity in neuronal morphology, electrophysiology, and gene expression, a robust metric of the coherence between different profiling modalities leading to a unified classification is still largely missing. Focusing on GABAergic neurons of the cerebral cortex, Gouwens et al.1 pioneered the first integrated cell-type classification based on the simultaneous analysis of the transcriptional networks, the recording of intrinsic electrophysiological properties, and the reconstruction of 3D morphologies of the same cell. Their comprehensive and high-quality data provide a new framework to shed light on what may be considered a "neuronal cell type."

Threat history controls flexible escape behavior in mice.

In many instances, external sensory-evoked neuronal activity is used by the brain to select the most appropriate behavioral response. Predator-avoidance behaviors such as freezing and escape1,2 are of particular interest since these stimulus-evoked responses are behavioral manifestations of a decision-making process that is fundamental to survival.3,4 Over the lifespan of an individual, however, the threat value of agents in the environment is believed to undergo constant revision,5 and in some cases, repeated avoidance of certain stimuli may no longer be an optimal behavioral strategy.6 To begin to study this type of adaptive control of decision-making, we devised an experimental paradigm to probe the properties of threat escape in the laboratory mouse Mus musculus. First, we found that while robust escape to visual looming stimuli can be observed after 2 days of social isolation, mice can also rapidly learn that such stimuli are non-threatening. This learned suppression of escape (LSE) is extremely robust and can persist for weeks and is not a generalized adaptation, since flight responses to novel live prey and auditory threat stimuli in the same environmental context were maintained. We also show that LSE cannot be explained by trial number or a simple form of stimulus desensitization since it is dependent on threat-escape history. We propose that the action selection process mediating escape behavior is constantly updated by recent threat history and that LSE can be used as a robust model system to understand the neurophysiological mechanisms underlying experience-dependent decision-making.

Accurate determination of marker location within whole-brain microscopy images.

High-resolution whole-brain microscopy provides a means for post hoc determination of the location of implanted devices and labelled cell populations that are necessary to interpret in vivo experiments designed to understand brain function. Here we have developed two plugins (brainreg and brainreg-segment) for the Python-based image viewer napari, to accurately map any object in a common coordinate space. We analysed the position of dye-labelled electrode tracks and two-photon imaged cell populations expressing fluorescent proteins. The precise location of probes and cells were physiologically interrogated and revealed accurate segmentation with near-cellular resolution.

Mesoscale microscopy and image analysis tools for understanding the brain.

Over the last ten years, developments in whole-brain microscopy now allow for high-resolution imaging of intact brains of small animals such as mice. These complex images contain a wealth of information, but many neuroscience laboratories do not have all of the computational knowledge and tools needed to process these data. We review recent open source tools for registration of images to atlases, and the segmentation, visualisation and analysis of brain regions and labelled structures such as neurons. Since the field lacks fully integrated analysis pipelines for all types of whole-brain microscopy analysis, we propose a pathway for tool developers to work together to meet this challenge.

Multisensory coding of angular head velocity in the retrosplenial cortex.

To successfully navigate the environment, animals depend on their ability to continuously track their heading direction and speed. Neurons that encode angular head velocity (AHV) are fundamental to this process, yet the contribution of various motion signals to AHV coding in the cortex remains elusive. By performing chronic single-unit recordings in the retrosplenial cortex (RSP) of the mouse and tracking the activity of individual AHV cells between freely moving and head-restrained conditions, we find that vestibular inputs dominate AHV signaling. Moreover, the addition of visual inputs onto these neurons increases the gain and signal-to-noise ratio of their tuning during active exploration. Psychophysical experiments and neural decoding further reveal that vestibular-visual integration increases the perceptual accuracy of angular self-motion and the fidelity of its representation by RSP ensembles. We conclude that while cortical AHV coding requires vestibular input, where possible, it also uses vision to optimize heading estimation during navigation.

A deep learning algorithm for 3D cell detection in whole mouse brain image datasets.

Understanding the function of the nervous system necessitates mapping the spatial distributions of its constituent cells defined by function, anatomy or gene expression. Recently, developments in tissue preparation and microscopy allow cellular populations to be imaged throughout the entire rodent brain. However, mapping these neurons manually is prone to bias and is often impractically time consuming. Here we present an open-source algorithm for fully automated 3D detection of neuronal somata in mouse whole-brain microscopy images using standard desktop computer hardware. We demonstrate the applicability and power of our approach by mapping the brain-wide locations of large populations of cells labeled with cytoplasmic fluorescent proteins expressed via retrograde trans-synaptic viral infection.

Analysis of segmentation ontology reveals the similarities and differences in connectivity onto L2/3 neurons in mouse V1.

Quantitatively comparing brain-wide connectivity of different types of neuron is of vital importance in understanding the function of the mammalian cortex. Here we have designed an analytical approach to examine and compare datasets from hierarchical segmentation ontologies, and applied it to long-range presynaptic connectivity onto excitatory and inhibitory neurons, mainly located in layer 2/3 (L2/3), of mouse primary visual cortex (V1). We find that the origins of long-range connections onto these two general cell classes-as well as their proportions-are quite similar, in contrast to the inputs on to a cell type in L6. These anatomical data suggest that distal inputs received by the general excitatory and inhibitory classes of neuron in L2/3 overlap considerably.

Visualizing anatomically registered data with brainrender.

Three-dimensional (3D) digital brain atlases and high-throughput brain-wide imaging techniques generate large multidimensional datasets that can be registered to a common reference frame. Generating insights from such datasets depends critically on visualization and interactive data exploration, but this a challenging task. Currently available software is dedicated to single atlases, model species or data types, and generating 3D renderings that merge anatomically registered data from diverse sources requires extensive development and programming skills. Here, we present brainrender: an open-source Python package for interactive visualization of multidimensional datasets registered to brain atlases. Brainrender facilitates the creation of complex renderings with different data types in the same visualization and enables seamless use of different atlas sources. High-quality visualizations can be used interactively and exported as high-resolution figures and animated videos. By facilitating the visualization of anatomically registered data, brainrender should accelerate the analysis, interpretation, and dissemination of brain-wide multidimensional data.

Cortical circuits for integration of self-motion and visual-motion signals.

The cerebral cortex contains cells which respond to movement of the head, and these cells are thought to be involved in the perception of self-motion. In particular, studies in the primary visual cortex of mice show that both running speed and passive whole-body rotation modulates neuronal activity, and modern genetically targeted viral tracing approaches have begun to identify previously unknown circuits that underlie these responses. Here we review recent experimental findings and provide a road map for future work in mice to elucidate the functional architecture and emergent properties of a cortical network potentially involved in the generation of egocentric-based visual representations for navigation.

Visual Experience Regulates the Intrinsic Excitability of Visual Cortical Neurons to Maintain Sensory Function.

This in vivo study shows that both intrinsic and sensory-evoked synaptic properties of layer 2/3 neurons in mouse visual cortex are modified by ongoing visual input. Following visual deprivation, intrinsic properties are significantly altered, although orientation selectivity across the population remains unchanged. We, therefore, suggest that cortical cells adjust their intrinsic excitability in an activity-dependent manner to compensate for changes in synaptic drive and maintain sensory network function.

Quantitative Association of Anatomical and Functional Classes of Olfactory Bulb Neurons.

Juxtaglomerular cells (JGCs) of the olfactory bulb (OB) glomerular layer (GL) play a fundamental role in olfactory information processing. Their variability in morphology, physiology, and connectivity suggests distinct functions. The quantitative understanding of population-wise morphological and physiological properties and a comprehensive classification based on quantitative parameters, however, is still lacking, impeding the analysis of microcircuits. Here, we provide multivariate clustering of 95 in vitro sampled cells from the GL of the mouse (male or female C57BL/6) OB and perform detailed morphological and physiological characterization for the seven computed JGC types. Using a classifier based on a subselection of parameters, we identified the neuron types in paired recordings to characterize their functional connectivity. We found that 4 of the 7 clusters comply with prevailing concepts of GL cell types, whereas the other 3 represent own distinct entities. We have labeled these entities horizontal superficial tufted cell (hSTC), vertical superficial tufted cell, and microglomerular cell (MGC): The hSTC is a tufted cell with a lateral dendrite that much like mitral cells and tufted cells receives excitatory inputs from the external tufted cell but likewise serves as an excitatory element for glomerular interneurons. The vertical superficial tufted cell, on the other hand, represents a tufted cell type with vertically projecting basal dendrites. We further define the MGC, characterized by a small dendritic tree and plateau action potentials. In addition to olfactory nerve-driven and external tufted cell driven interneurons, these MGCs represent a third functionally distinct type, the hSTC-driven interneurons. The presented correlative analysis helps to bridge the gap between branching patterns and cellular functional properties, permitting the integration of results from in vivo recordings, advanced morphological tools, and connectomics.SIGNIFICANCE STATEMENT The variance of neuron properties is a feature across mammalian cerebral circuits, contributing to signal processing and adding computational robustness to the networks. It is particularly noticeable in the glomerular layer of the olfactory bulb, the first site of olfactory information processing. We provide the first unbiased population-wise multivariate analysis to correlate morphological and physiological parameters of juxtaglomerular cells. We identify seven cell types, including four previously described neuron types, and identify further three distinct classes. The presented correlative analysis of morphological and physiological parameters gives an opportunity to predict morphological classes from physiological measurements or the functional properties of neurons from morphology and opens the way to integrate results from in vivo recordings, advanced morphological tools, and connectomics.

A Circuit for Integration of Head- and Visual-Motion Signals in Layer 6 of Mouse Primary Visual Cortex.

To interpret visual-motion events, the underlying computation must involve internal reference to the motion status of the observer's head. We show here that layer 6 (L6) principal neurons in mouse primary visual cortex (V1) receive a diffuse, vestibular-mediated synaptic input that signals the angular velocity of horizontal rotation. Behavioral and theoretical experiments indicate that these inputs, distributed over a network of 100 L6 neurons, provide both a reliable estimate and, therefore, physiological separation of head-velocity signals. During head rotation in the presence of visual stimuli, L6 neurons exhibit postsynaptic responses that approximate the arithmetic sum of the vestibular and visual-motion response. Functional input mapping reveals that these internal motion signals arrive into L6 via a direct projection from the retrosplenial cortex. We therefore propose that visual-motion processing in V1 L6 is multisensory and contextually dependent on the motion status of the animal's head.

aMAP is a validated pipeline for registration and segmentation of high-resolution mouse brain data.

The validation of automated image registration and segmentation is crucial for accurate and reliable mapping of brain connectivity and function in three-dimensional (3D) data sets. While validation standards are necessarily high and routinely met in the clinical arena, they have to date been lacking for high-resolution microscopy data sets obtained from the rodent brain. Here we present a tool for optimized automated mouse atlas propagation (aMAP) based on clinical registration software (NiftyReg) for anatomical segmentation of high-resolution 3D fluorescence images of the adult mouse brain. We empirically evaluate aMAP as a method for registration and subsequent segmentation by validating it against the performance of expert human raters. This study therefore establishes a benchmark standard for mapping the molecular function and cellular connectivity of the rodent brain.

Widespread vestibular activation of the rodent cortex.

Much of our understanding of the neuronal mechanisms of spatial navigation is derived from chronic recordings in rodents in which head-direction, place, and grid cells have all been described. However, despite the proposed importance of self-reference information to these internal representations of space, their congruence with vestibular signaling remains unclear. Here we have undertaken brain-wide functional mapping using both fMRI and electrophysiological methods to directly determine the spatial extent, strength, and time course of vestibular signaling across the rat forebrain. We find distributed activity throughout thalamic, limbic, and particularly primary sensory cortical areas in addition to known head-direction pathways. We also observe activation of frontal regions, including infralimbic and cingulate cortices, indicating integration of vestibular information throughout functionally diverse cortical regions. These whole-brain activity maps therefore suggest a widespread contribution of vestibular signaling to a self-centered framework for multimodal sensorimotor integration in support of movement planning, execution, spatial navigation, and autonomic responses to gravito-inertial changes.

Synaptic diversity enables temporal coding of coincident multisensory inputs in single neurons.

The ability of the brain to rapidly process information from multiple pathways is critical for reliable execution of complex sensory-motor behaviors, yet the cellular mechanisms underlying a neuronal representation of multimodal stimuli are poorly understood. Here we explored the possibility that the physiological diversity of mossy fiber (MF) to granule cell (GC) synapses in the mouse vestibulocerebellum may contribute to the processing of coincident multisensory information at the level of individual GCs. We found that the strength and short-term dynamics of individual MF-GC synapses can act as biophysical signatures for primary vestibular, secondary vestibular and visual input pathways. Most GCs receive inputs from different modalities, which, when coactivated, produced enhanced GC firing rates and distinct first spike latencies. Thus, pathway-specific synaptic response properties permit temporal coding of correlated multisensory inputs by single GCs, thereby enriching sensory representation and facilitating pattern separation.

The stimulus selectivity and connectivity of layer six principal cells reveals cortical microcircuits underlying visual processing.

Sensory computations performed in the neocortex involve layer six (L6) cortico-cortical (CC) and cortico-thalamic (CT) signaling pathways. Developing an understanding of the physiological role of these circuits requires dissection of the functional specificity and connectivity of the underlying individual projection neurons. By combining whole-cell recording from identified L6 principal cells in the mouse primary visual cortex (V1) with modified rabies virus-based input mapping, we have determined the sensory response properties and upstream monosynaptic connectivity of cells mediating the CC or CT pathway. We show that CC-projecting cells encompass a broad spectrum of selectivity to stimulus orientation and are predominantly innervated by deep layer V1 neurons. In contrast, CT-projecting cells are ultrasparse firing, exquisitely tuned to orientation and direction information, and receive long-range input from higher cortical areas. This segregation in function and connectivity indicates that L6 microcircuits route specific contextual and stimulus-related information within and outside the cortical network.

Sensory-evoked synaptic integration in cerebellar and cerebral cortical neurons.

Neurons integrate synaptic inputs across time and space, a process that determines the transformation of input signals into action potential output. This article explores how synaptic integration contributes to the richness of sensory signalling in the cerebellar and cerebral cortices. Whether a neuron receives a few or a few thousand discrete inputs, most evoked synaptic activity generates only subthreshold membrane potential fluctuations. Sensory tuning of synaptic inputs is typically broad, but short-term dynamics and the interplay between excitation and inhibition restrict action potential firing to narrow windows of opportunity. We highlight the challenges and limitations of the use of somatic recordings in the study of synaptic integration and the importance of active dendritic mechanisms in sensory processing.