Automated computation of arbor densities: a step toward identifying neuronal cell types

A community-based transcriptomics classification and nomenclature of neocortical cell types

To understand the function of cortical circuits, it is necessary to catalog their cellular diversity. Past attempts to do so using anatomical, physiological or molecular features of cortical cells have not resulted in a unified taxonomy of neuronal or glial cell types, partly due to limited data. Single-cell transcriptomics is enabling, for the first time, systematic high-throughput measurements of cortical cells and generation of datasets that hold the promise of being complete, accurate and permanent. Statistical analyses of these data reveal clusters that often correspond to cell types previously defined by morphological or physiological criteria and that appear conserved across cortical areas and species. To capitalize on these new methods, we propose the adoption of a transcriptome-based taxonomy of cell types for mammalian neocortex. This classification should be hierarchical and use a standardized nomenclature. It should be based on a probabilistic definition of a cell type and incorporate data from different approaches, developmental stages and species. A community-based classification and data aggregation model, such as a knowledge graph, could provide a common foundation for the study of cortical circuits. This community-based classification, nomenclature and data aggregation could serve as an example for cell type atlases in other parts of the body.

Density Visualization Pipeline: A Tool for Cellular and Network Density Visualization and Analysis

Neuron classification is an important component in analyzing network structure and quantifying the effect of neuron topology on signal processing. Current quantification and classification approaches rely on morphology projection onto lower-dimensional spaces. In this paper a 3D visualization and quantification tool is presented. The Density Visualization Pipeline (DVP) computes, visualizes and quantifies the density distribution, i.e., the "mass" of interneurons. We use the DVP to characterize and classify a set of GABAergic interneurons. Classification of GABAergic interneurons is of crucial importance to understand on the one hand their various functions and on the other hand their ubiquitous appearance in the neocortex. 3D density map visualization and projection to the one-dimensional x, y, z subspaces show a clear distinction between the studied cells, based on these metrics. The DVP can be coupled to computational studies of the behavior of neurons and networks, in which network topology information is derived from DVP information. The DVP reads common neuromorphological file formats, e.g., Neurolucida XML files, NeuroMorpho.org SWC files and plain ASCII files. Full 3D visualization and projections of the density to 1D and 2D manifolds are supported by the DVP. All routines are embedded within the visual programming IDE VRL-Studio for Java which allows the definition and rapid modification of analysis workflows.

Transgenic models for investigating the nervous system: Currently available neurofluorescent reporters and potential neuronal markers

Recombinant DNA technologies have enabled the development of transgenic animal models for use in studying a myriad of diseases and biological states. By placing fluorescent reporters under the direct regulation of the promoter region of specific marker proteins, these models can localize and characterize very specific cell types. One important application of transgenic species is the study of the cytoarchitecture of the nervous system. Neurofluorescent reporters can be used to study the structural patterns of nerves in the central or peripheral nervous system in vivo, as well as phenomena involving embryologic or adult neurogenesis, injury, degeneration, and recovery. Furthermore, crucial molecular factors can also be screened via the transgenic approach, which may eventually play a major role in the development of therapeutic strategies against diseases like Alzheimer's or Parkinson's. This review describes currently available reporters and their uses in the literature as well as potential neural markers that can be leveraged to create additional, robust transgenic models for future studies.

Inducible rodent models of glaucoma

Glaucoma is one of the leading causes of vision impairment worldwide. In order to further understand the molecular pathobiology of this disease and to develop better therapies, clinically relevant animal models are necessary. In recent years, both the rat and mouse have become popular models in glaucoma research. Key reasons are: many important biological similarities shared among rodent eyes and the human eye; development of improved methods to induce glaucoma and to evaluate glaucomatous damage; availability of genetic tools in the mouse; as well as the relatively low cost of rodent studies. Commonly studied rat and mouse glaucoma models include intraocular pressure (IOP)-dependent and pressure-independent models. The pressure-dependent models address the most important risk factor of elevated IOP, whereas the pressure-independent models assess "normal tension" glaucoma and other "non-IOP" related factors associated with glaucomatous damage. The current article provides descriptions of these models, their characterizations, specific techniques to induce glaucoma, mechanisms of injury, advantages, and limitations.

A projection specific logic to sampling visual inputs in mouse superior colliculus

Using sensory information to trigger different behaviors relies on circuits that pass through brain regions. The rules by which parallel inputs are routed to downstream targets are poorly understood. The superior colliculus mediates a set of innate behaviors, receiving input from >30 retinal ganglion cell types and projecting to behaviorally important targets including the pulvinar and parabigeminal nucleus. Combining transsynaptic circuit tracing with in vivo and ex vivo electrophysiological recordings, we observed a projection-specific logic where each collicular output pathway sampled a distinct set of retinal inputs. Neurons projecting to the pulvinar or the parabigeminal nucleus showed strongly biased sampling from four cell types each, while six others innervated both pathways. The visual response properties of retinal ganglion cells correlated well with those of their disynaptic targets. These findings open the possibility that projection-specific sampling of retinal inputs forms a basis for the selective triggering of behaviors by the superior colliculus.

Cellular properties of intrinsically photosensitive retinal ganglion cells during postnatal development

BACKGROUND

Melanopsin-expressing, intrinsically photosensitive retinal ganglion cells (ipRGCs) respond directly to light and have been shown to mediate a broad variety of visual behaviors in adult animals. ipRGCs are also the first light sensitive cells in the developing retina, and have been implicated in a number of retinal developmental processes such as pruning of retinal vasculature and refinement of retinofugal projections. However, little is currently known about the properties of the six ipRGC subtypes during development, and how these cells act to influence retinal development. We therefore sought to characterize the structure, physiology, and birthdate of the most abundant ipRGC subtypes, M1, M2, and M4, at discrete postnatal developmental timepoints.

METHODS

We utilized whole cell patch clamp to measure the electrophysiological and morphological properties of ipRGC subtypes through postnatal development. We also used EdU labeling to determine the embryonic timepoints at which ipRGC subtypes terminally differentiate.

RESULTS

Our data show that ipRGC subtypes are distinguishable from each other early in postnatal development. Additionally, we find that while ipRGC subtypes terminally differentiate at similar embryonic stages, the subtypes reach adult-like morphology and physiology at different developmental timepoints.

CONCLUSIONS

This work provides a broad assessment of ipRGC morphological and physiological properties during the postnatal stages at which they are most influential in modulating retinal development, and lays the groundwork for further understanding of the specific role of each ipRGC subtype in influencing retinal and visual system development.

Morphological Neuron Classification Based on Dendritic Tree Hierarchy

The shape of a neuron can reveal interesting properties about its function. Therefore, morphological neuron characterization can contribute to a better understanding of how the brain works. However, one of the great challenges of neuroanatomy is the definition of morphological properties that can be used for categorizing neurons. This paper proposes a new methodology for neuron morphological analysis by considering different hierarchies of the dendritic tree for characterizing and categorizing neuronal cells. The methodology consists in using different strategies for decomposing the dendritic tree along its hierarchies, allowing the identification of relevant parts (possibly related to specific neuronal functions) for classification tasks. A set of more than 5000 neurons corresponding to 10 classes were examined with supervised classification algorithms based on this strategy. It was found that classification accuracies similar to those obtained by using whole neurons can be achieved by considering only parts of the neurons. Branches close to the soma were found to be particularly relevant for classification.

The world of the identified or digital neuron

In general, neurons in insects and many other invertebrate groups are individually recognizable, enabling us to assign an index number to specific neurons in a manner which is rarely possible in a vertebrate brain. This endows many studies on insect nervous systems with the opportunity to document neurons with great precision, so that in favourable cases we can return to the same neuron or neuron type repeatedly so as to recognize many separate morphological classes. The visual system of the fly's compound eye particularly provides clear examples of the accuracy of neuron wiring, allowing numerical comparisons between representatives of the same cell type, and estimates of the accuracy of their wiring.

The BRAIN Initiative Cell Census Consortium: Lessons Learned toward Generating a Comprehensive Brain Cell Atlas

A comprehensive characterization of neuronal cell types, their distributions, and patterns of connectivity is critical for understanding the properties of neural circuits and how they generate behaviors. Here we review the experiences of the BRAIN Initiative Cell Census Consortium, ten pilot projects funded by the U.S. BRAIN Initiative, in developing, validating, and scaling up emerging genomic and anatomical mapping technologies for creating a complete inventory of neuronal cell types and their connections in multiple species and during development. These projects lay the foundation for a larger and longer-term effort to generate whole-brain cell atlases in species including mice and humans.

Whole-body tissue stabilization and selective extractions via tissue-hydrogel hybrids for high-resolution intact circuit mapping and phenotyping

To facilitate fine-scale phenotyping of whole specimens, we describe here a set of tissue fixation-embedding, detergent-clearing and staining protocols that can be used to transform excised organs and whole organisms into optically transparent samples within 1-2 weeks without compromising their cellular architecture or endogenous fluorescence. PACT (passive CLARITY technique) and PARS (perfusion-assisted agent release in situ) use tissue-hydrogel hybrids to stabilize tissue biomolecules during selective lipid extraction, resulting in enhanced clearing efficiency and sample integrity. Furthermore, the macromolecule permeability of PACT- and PARS-processed tissue hybrids supports the diffusion of immunolabels throughout intact tissue, whereas RIMS (refractive index matching solution) grants high-resolution imaging at depth by further reducing light scattering in cleared and uncleared samples alike. These methods are adaptable to difficult-to-image tissues, such as bone (PACT-deCAL), and to magnified single-cell visualization (ePACT). Together, these protocols and solutions enable phenotyping of subcellular components and tracing cellular connectivity in intact biological networks.

Function and Circuitry of VIP+ Interneurons in the Mouse Retina

Visual processing in the retina depends on coordinated signaling by interneurons. Photoreceptor signals are relayed to ∼20 ganglion cell types through a dozen excitatory bipolar interneurons, each responsive to light increments (ON) or decrements (OFF). ON and OFF bipolar cell pathways become tuned through specific connections with inhibitory interneurons: horizontal and amacrine cells. A major obstacle for understanding retinal circuitry is the unknown function of most of the ∼30-40 amacrine cell types, each of which synapses onto a subset of bipolar cell terminals, ganglion cell dendrites, and other amacrine cells. Here, we used a transgenic mouse line in which vasoactive intestinal polypeptide-expressing (VIP+) GABAergic interneurons express Cre recombinase. Targeted whole-cell recordings of fluorescently labeled VIP+ cells revealed three predominant types: wide-field bistratified and narrow-field monostratified cells with somas in the inner nuclear layer (INL) and medium-field monostratified cells with somas in the ganglion cell layer (GCL). Bistratified INL cells integrated excitation and inhibition driven by both ON and OFF pathways with little spatial tuning. Narrow-field INL cells integrated excitation driven by the ON pathway and inhibition driven by both pathways, with pronounced hyperpolarizations at light offset. Monostratified GCL cells integrated excitation and inhibition driven by the ON pathway and showed center-surround spatial tuning. Optogenetic experiments showed that, collectively, VIP+ cells made strong connections with OFF δ, ON-OFF direction-selective, and W3 ganglion cells but weak, inconsistent connections with ON and OFF α cells. Revealing VIP+ cell morphologies, receptive fields and synaptic connections advances our understanding of their role in visual processing.

SIGNIFICANCE STATEMENT

The retina is a model system for understanding nervous system function. At the first stage, rod and cone photoreceptors encode light and communicate with a complex network of interneurons. These interneurons drive the responses of ganglion cells, which form the optic nerve and transmit visual information to the brain. Presently, we lack information about many of the retina's inhibitory amacrine interneurons. In this study, we used genetically modified mice to study the light responses and intercellular connections of specific amacrine cell types. The results show diversity in the shape and function of the studied amacrine cells and elucidate their connections with specific types of ganglion cell. The findings advance our understanding of the cellular basis for retinal function.