The cell-type-specific spatial organization of the anterior thalamic nuclei of the mouse brain.

Understanding the cell-type composition and spatial organization of brain regions is crucial for interpreting brain computation and function. In the thalamus, the anterior thalamic nuclei (ATN) are involved in a wide variety of functions, yet the cell-type composition of the ATN remains unmapped at a single-cell and spatial resolution. Combining single-cell RNA sequencing, spatial transcriptomics, and multiplexed fluorescent in situ hybridization, we identify three discrete excitatory cell-type clusters that correspond to the known nuclei of the ATN and uncover marker genes, molecular pathways, and putative functions of these cell types. We further illustrate graded spatial variation along the dorsomedial-ventrolateral axis for all individual nuclei of the ATN and additionally demonstrate that the anteroventral nucleus exhibits spatially covarying protein products and long-range inputs. Collectively, our study reveals discrete and continuous cell-type organizational principles of the ATN, which will help to guide and interpret experiments on ATN computation and function.

Engram neurons: Encoding, consolidation, retrieval, and forgetting of memory.

Tremendous strides have been made in our understanding of the neurobiological substrates of memory - the so-called memory "engram". Here, we integrate recent progress in the engram field to illustrate how engram neurons transform across the "lifespan" of a memory - from initial memory encoding, to consolidation and retrieval, and ultimately to forgetting. To do so, we first describe how cell-intrinsic properties shape the initial emergence of the engram at memory encoding. Second, we highlight how these encoding neurons preferentially participate in synaptic- and systems-level consolidation of memory. Third, we describe how these changes during encoding and consolidation guide neural reactivation during retrieval, and facilitate memory recall. Fourth, we describe neurobiological mechanisms of forgetting, and how these mechanisms can counteract engram properties established during memory encoding, consolidation, and retrieval. Motivated by recent experimental results across these four sections, we conclude by proposing some conceptual extensions to the traditional view of the engram, including broadening the view of cell-type participation within engrams and across memory stages. In collection, our review synthesizes general principles of the engram across memory stages, and describes future avenues to further understand the dynamic engram.

Sharp cell-type-identity changes differentiate the retrosplenial cortex from the neocortex.

The laminae of the neocortex are fundamental processing layers of the mammalian brain. Notably, such laminae are believed to be relatively stereotyped across short spatial scales such that shared laminae between nearby brain regions exhibit similar constituent cells. Here, we consider a potential exception to this rule by studying the retrosplenial cortex (RSC), a brain region known for sharp cytoarchitectonic differences across its granular-dysgranular border. Using a variety of transcriptomics techniques, we identify, spatially map, and interpret the excitatory cell-type landscape of the mouse RSC. In doing so, we uncover that RSC gene expression and cell types change sharply at the granular-dysgranular border. Additionally, supposedly homologous laminae between the RSC and the neocortex are effectively wholly distinct in their cell-type composition. In collection, the RSC exhibits a variety of intrinsic cell-type specializations and embodies an organizational principle wherein cell-type identities can vary sharply within and between brain regions.

Neuronal cell types, projections, and spatial organization of the central amygdala.

The central amygdala (CEA) has been richly studied for interpreting function and behavior according to specific cell types and circuits. Such work has typically defined molecular cell types by classical inhibitory marker genes; consequently, whether marker-gene-defined cell types exhaustively cover the CEA and co-vary with connectivity remains unresolved. Here, we combined single-cell RNA sequencing, multiplexed fluorescent in situ hybridization, immunohistochemistry, and long-range projection mapping to derive a "bottom-up" understanding of CEA cell types. In doing so, we identify two major cell types, encompassing one-third of all CEA neurons, that have gone unresolved in previous studies. In spatially mapping these novel types, we identify a non-canonical CEA subdomain associated with Nr2f2 expression and uncover an Isl1-expressing medial cell type that accounts for many long-range CEA projections. Our results reveal new CEA organizational principles across cell types and spatial scales and provide a framework for future work examining cell-type-specific behavior and function.

Spatially patterned excitatory neuron subtypes and projections of the claustrum.

The claustrum is a functionally and structurally complex brain region, whose very spatial extent remains debated. Histochemical-based approaches typically treat the claustrum as a relatively narrow anatomical region that primarily projects to the neocortex, whereas circuit-based approaches can suggest a broader claustrum region containing projections to the neocortex and other regions. Here, in the mouse, we took a bottom-up and cell-type-specific approach to complement and possibly unite these seemingly disparate conclusions. Using single-cell RNA-sequencing, we found that the claustrum comprises two excitatory neuron subtypes that are differentiable from the surrounding cortex. Multicolor retrograde tracing in conjunction with 12-channel multiplexed in situ hybridization revealed a core-shell spatial arrangement of these subtypes, as well as differential downstream targets. Thus, the claustrum comprises excitatory neuron subtypes with distinct molecular and projection properties, whose spatial patterns reflect the narrower and broader claustral extents debated in previous research. This subtype-specific heterogeneity likely shapes the functional complexity of the claustrum.

Elucidating memory in the brain via single-cell transcriptomics.

Elucidating the neural mechanisms of memory in the brain is a central goal of neuroscience. Here, we discuss modern-day transcriptomics methodologies, and how they are well-poised to revolutionize our insight into memory mechanisms at unprecedented resolution and throughput. Focusing on the hippocampus and amygdala, two regions extensively examined in memory research, we show how single-cell transcriptomics technologies have been leveraged to understand the naïve state of these brain regions. Building upon this foundation, we show that these technologies can be applied to single-trial learning paradigms to comprehensively identify molecules and cells that participate in the encoding and retrieval of memory. Transcriptomics also provides an opportunity to understand the cell-type organization of the human hippocampus and amygdala, and due to conservation of these brain regions between humans and rodents, to infer behavioral and causal contributions in the human brain by leveraging rodent cell-type homologies and interventions. Ultimately, such transcriptomic technologies are poised to usher in a qualitatively novel understanding of memory in the brain.

Extensive and spatially variable within-cell-type heterogeneity across the basolateral amygdala.

The basolateral amygdala complex (BLA), extensively connected with both local amygdalar nuclei as well as long-range circuits, is involved in a diverse array of functional roles. Understanding the mechanisms of such functional diversity will be greatly informed by understanding the cell-type-specific landscape of the BLA. Here, beginning with single-cell RNA sequencing, we identified both discrete and graded continuous gene-expression differences within the mouse BLA. Via in situ hybridization, we next mapped this discrete transcriptomic heterogeneity onto a sharp spatial border between the basal and lateral amygdala nuclei, and identified continuous spatial gene-expression gradients within each of these regions. These discrete and continuous spatial transformations of transcriptomic cell-type identity were recapitulated by local morphology as well as long-range connectivity. Thus, BLA excitatory neurons are a highly heterogenous collection of neurons that spatially covary in molecular, cellular, and circuit properties. This heterogeneity likely drives pronounced spatial variation in BLA computation and function.

A Sparse, Spatially Biased Subtype of Mature Granule Cell Dominates Recruitment in Hippocampal-Associated Behaviors.

Animals can store information about experiences by activating specific neuronal populations, and subsequent reactivation of these neural ensembles can lead to recall of salient experiences. In the hippocampus, granule cells of the dentate gyrus participate in such memory engrams; however, whether there is an underlying logic to granule cell participation has not been examined. Here, we find that a range of novel experiences preferentially activates granule cells of the suprapyramidal blade relative to the infrapyramidal blade. Motivated by this, we identify a suprapyramidal-blade-enriched population of granule cells with distinct spatial, morphological, physiological, and developmental properties. Via transcriptomics, we map these traits onto a sparse and discrete granule cell subtype that is recruited at a 10-fold greater frequency than expected by subtype prevalence, constituting the majority of all recruited granule cells. Thus, in behaviors known to involve hippocampal-dependent memory formation, a rare and spatially localized subtype dominates overall granule cell recruitment.

Single-cell transcriptomics as a framework and roadmap for understanding the brain.

A framework for interpreting and guiding experimental examination of the brain is essential for neuroscience. Recently, single-cell RNA sequencing and single-molecule fluorescent in situ hybridization have emerged as key technologies to generate such a framework at a single-cell resolution. These technologies provide a powerful complement for understanding gene expression in the brain: RNA sequencing enables genome-wide high-throughput quantification of gene expression, and in situ hybridization yields spatial registration of gene expression at a cellular resolution. Here, I discuss the insight that each of these technologies individually provide, and how they can be paired in principle and practice to resolve the cell-type-specific spatial organization of the brain. I further discuss the potential of cutting-edge spatial transcriptomics technologies that leverage the advantages of both techniques within the same assay, as well as how transcriptomic assays can be linked with higher-order features of brain structure and function. Such current and forthcoming transcriptomic technologies will have immense impact in generating an underlying logic of the nervous system, and will guide experiments and interpretations across molecular, cellular, circuit, and behavioural neuroscience.

Heterogeneity within classical cell types is the rule: lessons from hippocampal pyramidal neurons.

The mechanistic operation of brain regions is often interpreted by partitioning constituent neurons into 'cell types'. Historically, such cell types were broadly defined by their correspondence to gross features of the nervous system (such as cytoarchitecture). Modern-day neuroscientific techniques, enabling a more nuanced examination of neuronal properties, have illustrated a wealth of heterogeneity within these classical cell types. Here, we review the extent of this within-cell-type heterogeneity in one of the simplest cortical regions of the mammalian brain, the rodent hippocampus. We focus on the mounting evidence that the classical CA3, CA1 and subiculum pyramidal cell types all exhibit prominent and spatially patterned within-cell-type heterogeneity, and suggest these cell types provide a model system for exploring the organization and function of such heterogeneity. Given that the hippocampus is structurally simple and evolutionarily ancient, within-cell-type heterogeneity is likely to be a general and crucial feature of the mammalian brain.

The subiculum is a patchwork of discrete subregions.

In the hippocampus, the classical pyramidal cell type of the subiculum acts as a primary output, conveying hippocampal signals to a diverse suite of downstream regions. Accumulating evidence suggests that the subiculum pyramidal cell population may actually be comprised of discrete subclasses. Here, we investigated the extent and organizational principles governing pyramidal cell heterogeneity throughout the mouse subiculum. Using single-cell RNA-seq, we find that the subiculum pyramidal cell population can be deconstructed into eight separable subclasses. These subclasses were mapped onto abutting spatial domains, ultimately producing a complex laminar and columnar organization with heterogeneity across classical dorsal-ventral, proximal-distal, and superficial-deep axes. We further show that these transcriptomically defined subclasses correspond to differential protein products and can be associated with specific projection targets. This work deconstructs the complex landscape of subiculum pyramidal cells into spatially segregated subclasses that may be observed, controlled, and interpreted in future experiments.

Dissociable Structural and Functional Hippocampal Outputs via Distinct Subiculum Cell Classes.

The mammalian hippocampus, comprised of serially connected subfields, participates in diverse behavioral and cognitive functions. It has been postulated that parallel circuitry embedded within hippocampal subfields may underlie such functional diversity. We sought to identify, delineate, and manipulate this putatively parallel architecture in the dorsal subiculum, the primary output subfield of the dorsal hippocampus. Population and single-cell RNA-seq revealed that the subiculum can be divided into two spatially adjacent subregions associated with prominent differences in pyramidal cell gene expression. Pyramidal cells occupying these two regions differed in their long-range inputs, local wiring, projection targets, and electrophysiological properties. Leveraging gene-expression differences across these regions, we use genetically restricted neuronal silencing to show that these regions differentially contribute to spatial working memory. This work provides a coherent molecular-, cellular-, circuit-, and behavioral-level demonstration that the hippocampus embeds structurally and functionally dissociable streams within its serial architecture.

Continuous Variation within Cell Types of the Nervous System.

The brain is an organ of immense complexity. Next-generation RNA sequencing (RNA-seq) is becoming increasingly popular in the deconstruction of this complexity into distinct classes of 'cell types'. Notably, in addition to revealing the organization of this distinct cell-type landscape, the technology has also begun to illustrate that continuous variation can be found within narrowly defined cell types. Here we summarize the evidence for graded transcriptomic heterogeneity being present, widespread, and functionally relevant in the nervous system. We explain how these graded differences can map onto higher-order organizational features and how they may reframe existing interpretations of higher-order heterogeneity. Ultimately, a multimodal approach incorporating continuously variable cell types will facilitate an accurate reductionist interpretation of the nervous system.

Single excitatory axons form clustered synapses onto CA1 pyramidal cell dendrites.

CA1 pyramidal neurons are a major output of the hippocampus and encode features of experience that constitute episodic memories. Feature-selective firing of these neurons results from the dendritic integration of inputs from multiple brain regions. While it is known that synchronous activation of spatially clustered inputs can contribute to firing through the generation of dendritic spikes, there is no established mechanism for spatiotemporal synaptic clustering. Here we show that single presynaptic axons form multiple, spatially clustered inputs onto the distal, but not proximal, dendrites of CA1 pyramidal neurons. These compound connections exhibit ultrastructural features indicative of strong synapses and occur much more commonly in entorhinal than in thalamic afferents. Computational simulations revealed that compound connections depolarize dendrites in a biophysically efficient manner, owing to their inherent spatiotemporal clustering. Our results suggest that distinct afferent projections use different connectivity motifs that differentially contribute to dendritic integration.

Integrating Results across Methodologies Is Essential for Producing Robust Neuronal Taxonomies.

Elucidating the diversity and spatial organization of cell types in the brain is an essential goal of neuroscience, with many emerging technologies helping to advance this endeavor. Using a new in situ hybridization method that can measure the expression of hundreds of genes in a given mouse brain section (amplified seqFISH), Shah et al. (2016) describe a spatial organization of hippocampal cell types that differs from previous reports. In seeking to understand this discrepancy, we find that many of the barcoded genes used by seqFISH to characterize this spatial organization, when cross-validated by other sensitive methodologies, exhibit negligible expression in the hippocampus. Additionally, the results of Shah et al. (2016) do not recapitulate canonical cellular hierarchies and improperly classify major neuronal cell types. We suggest that, when describing the spatial organization of brain regions, cross-validation using multiple techniques should be used to yield robust and informative cellular classification. This Matters Arising paper is in response to Shah et al. (2016), published in Neuron. See also the response by Shah et al. (2017), published in this issue.

Illuminating the Neuronal Architecture Underlying Context in Fear Memory.

Context plays a foundational role in determining how to interpret potentially fear-producing stimuli, yet the precise neurobiological substrates of context are poorly understood. In this issue of Cell, Xu et al. elegantly show that parallel neuronal circuits are necessary for two distinct roles of context in fear conditioning.

Hipposeq: a comprehensive RNA-seq database of gene expression in hippocampal principal neurons.

Clarifying gene expression in narrowly defined neuronal populations can provide insight into cellular identity, computation, and functionality. Here, we used next-generation RNA sequencing (RNA-seq) to produce a quantitative, whole genome characterization of gene expression for the major excitatory neuronal classes of the hippocampus; namely, granule cells and mossy cells of the dentate gyrus, and pyramidal cells of areas CA3, CA2, and CA1. Moreover, for the canonical cell classes of the trisynaptic loop, we profiled transcriptomes at both dorsal and ventral poles, producing a cell-class- and region-specific transcriptional description for these populations. This dataset clarifies the transcriptional properties and identities of lesser-known cell classes, and moreover reveals unexpected variation in the trisynaptic loop across the dorsal-ventral axis. We have created a public resource, Hipposeq (http://hipposeq.janelia.org), which provides analysis and visualization of these data and will act as a roadmap relating molecules to cells, circuits, and computation in the hippocampus.

Structured Dendritic Inhibition Supports Branch-Selective Integration in CA1 Pyramidal Cells.

Neuronal circuit function is governed by precise patterns of connectivity between specialized groups of neurons. The diversity of GABAergic interneurons is a hallmark of cortical circuits, yet little is known about their targeting to individual postsynaptic dendrites. We examined synaptic connectivity between molecularly defined inhibitory interneurons and CA1 pyramidal cell dendrites using correlative light-electron microscopy and large-volume array tomography. We show that interneurons can be highly selective in their connectivity to specific dendritic branch types and, furthermore, exhibit precisely targeted connectivity to the origin or end of individual branches. Computational simulations indicate that the observed subcellular targeting enables control over the nonlinear integration of synaptic input or the initiation and backpropagation of action potentials in a branch-selective manner. Our results demonstrate that connectivity between interneurons and pyramidal cell dendrites is more precise and spatially segregated than previously appreciated, which may be a critical determinant of how inhibition shapes dendritic computation.

Spatial Gene-Expression Gradients Underlie Prominent Heterogeneity of CA1 Pyramidal Neurons.

Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types. This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but it may be further hampered by prominent within-class variability. Here, we considered a well-defined canonical neuronal population­hippocampal CA1 pyramidal cells (CA1 PCs)­and systematically examined the extent and spatial rules of transcriptional heterogeneity. Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences within CA1 along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous gene-expression gradients, producing a transcriptional profile consistent with a multifarious continuum of cells. This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits.