Integrating Results across Methodologies Is Essential for Producing Robust Neuronal Taxonomies

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.

Multimodal determinants of phase-locked dynamics across deep-superficial hippocampal sublayers during theta oscillations

Theta oscillations play a major role in temporarily defining the hippocampal rate code by translating behavioral sequences into neuronal representations. However, mechanisms constraining phase timing and cell-type-specific phase preference are unknown. Here, we employ computational models tuned with evolutionary algorithms to evaluate phase preference of individual CA1 pyramidal cells recorded in mice and rats not engaged in any particular memory task. We applied unbiased and hypothesis-free approaches to identify effects of intrinsic and synaptic factors, as well as cell morphology, in determining phase preference. We found that perisomatic inhibition delivered by complementary populations of basket cells interacts with input pathways to shape phase-locked specificity of deep and superficial pyramidal cells. Somatodendritic integration of fluctuating glutamatergic inputs defined cycle-by-cycle by unsupervised methods demonstrated that firing selection is tuneable across sublayers. Our data identify different mechanisms of phase-locking selectivity that are instrumental for flexible dynamical representations of theta sequences.

Theta oscillations have been implicated in hippocampal processing but mechanisms constraining phase timing of specific cell types are unknown. Here, the authors combine single-cell and multisite recordings with evolutionary computational models to evaluate mechanisms of phase preference of deep and superficial CA1 pyramidal cells.

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.

Probabilistic cell typing enables fine mapping of closely related cell types in situ

Understanding the function of a tissue requires knowing the spatial organization of its constituent cell types. In the cerebral cortex, single-cell RNA sequencing (scRNA-seq) has revealed the genome-wide expression patterns that define its many, closely related neuronal types, but cannot reveal their spatial arrangement. Here we introduce probabilistic cell typing by in situ sequencing (pciSeq), an approach that leverages prior scRNA-seq classification to identify cell types using multiplexed in situ RNA detection. We applied this method by mapping the inhibitory neurons of hippocampal area CA1, for which ground truth is available from extensive prior work identifying their laminar organization. Our method identified these closely related classes in a spatial arrangement matching ground truth, and further identified multiple classes of isocortical pyramidal cell in a pattern matching their known organization. This method will allow identifying the spatial organization of fine cell types across the brain and other tissues.

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.

Integration of gene expression and brain-wide connectivity reveals the multiscale organization of mouse hippocampal networks

Understanding the organization of the hippocampus is fundamental to understanding brain function related to learning, memory, emotions, and diseases like Alzheimer’s disease. Physiological studies in humans and rodents suggest both structural and functional heterogeneity along the longitudinal axis of the hippocampus. Yet the recent discovery of discrete gene expression domains within the mouse hippocampus has provided the opportunity to re-evaluate hippocampal connectivity. To integrate mouse hippocampal gene expression and connectivity, we mapped the distribution of distinct gene expression patterns within mouse hippocampus and subiculum to create the Hippocampus Gene Expression Atlas (HGEA). Notably, novel subiculum gene expression patterns revealed a hidden laminar organization. Guided by the HGEA, we constructed the most detailed hippocampal connectome available using Mouse Connectome Project (www.MouseConnectome.org) tract tracing data. Our results define the hippocampus’ multiscale network organization and demonstrate each subnetwork’s unique brain-wide connectivity patterns.

From Tissues to Cell Types and Back: Single-Cell Gene Expression Analysis of Tissue Architecture

With the recent transformative developments in single-cell genomics and, in particular, single-cell gene expression analysis, it is now possible to study tissues at the single-cell level, rather than having to rely on data from bulk measurements. Here we review the rapid developments in single-cell RNA sequencing (scRNA-seq) protocols that have the potential for unbiased identification and profiling of all cell types within a tissue or organism. In addition, novel approaches for spatial profiling of gene expression allow us to map individual cells and cell types back into the three-dimensional context of organs. The combination of in-depth single-cell and spatial gene expression data will reveal tissue architecture in unprecedented detail, generating a wealth of biological knowledge and a better understanding of many diseases.

CA1 pyramidal cell diversity enabling parallel information processing in the hippocampus

Hippocampal network operations supporting spatial navigation and declarative memory are traditionally interpreted in a framework where each hippocampal area, such as the dentate gyrus, CA3, and CA1, consists of homogeneous populations of functionally equivalent principal neurons. However, heterogeneity within hippocampal principal cell populations, in particular within pyramidal cells at the main CA1 output node, is increasingly recognized and includes developmental, molecular, anatomical, and functional differences. Here we review recent progress in the delineation of hippocampal principal cell subpopulations by focusing on radially defined subpopulations of CA1 pyramidal cells, and we consider how functional segregation of information streams, in parallel channels with nonuniform properties, could represent a general organizational principle of the hippocampus supporting diverse behaviors.

The promise of spatial transcriptomics for neuroscience in the era of molecular cell typing

The stereotyped spatial architecture of the brain is both beautiful and fundamentally related to its function, extending from gross morphology to individual neuron types, where soma position, dendritic architecture, and axonal projections determine their roles in functional circuitry. Our understanding of the cell types that make up the brain is rapidly accelerating, driven in particular by recent advances in single-cell transcriptomics. However, understanding brain function, development, and disease will require linking molecular cell types to morphological, physiological, and behavioral correlates. Emerging spatially resolved transcriptomic methods promise to fill this gap by localizing molecularly defined cell types in tissues, with simultaneous detection of morphology, activity, or connectivity. Here, we review the requirements for spatial transcriptomic methods toward these goals, consider the challenges ahead, and describe promising applications.

Temporal Lobe Epilepsy, Stroke, and Traumatic Brain Injury: Mechanisms of Hyperpolarized, Depolarized, and Flow-Through Ion Channels Utilized as Tri-Coordinate Biomarkers of Electrophysiologic Dysfunction

The brain is an integrated network of multiple variables that when compromised create a diseased state. The neuropathology of temporal lobe epilepsy (TLE), stroke, and traumatic brain injury (TBI) demonstrate both similarity and complexity that reflects this integrated variability; TLE with its live human tissue resection provides opportunity for translational science to demonstrate scale equivalent experimentation between the macroscopic world of clinical disease and the microscopic world of basic science. The extended value of this research is that the neuroinflammatory abnormalities that occur throughout astrocytes with hippocampal sclerosis and damaged or even reversed signaling pathways (inhibition to excitation such as with gaba-aminobutyric acid) are similar to those seen in post-stroke and TBI models. In evaluation of the epilepsy population this interconnectedness of pathology warrants further evaluation with collaborative efforts. This review summarizes patterns that could shift experimentation closer to the macro level of humanity, but still represent the micro world of genetics, epigenetics, and neuro-injury across etiologies of physiologic dysfunction such as TLE, stroke, and TBI with evaluation of cell function using electrophysiology. In conclusion we demonstrate the plausibility of electrophysiologic voltage and current measurement of brain tissue by patch clamp analysis to specify actual electrophysiologic function for comparison to electroencephalography in order to aid neurologic evaluation. Finally, we discuss the opportunity with multiscale modeling to display integration of the hyperpolarization cyclic-nucleotide gated channel, the depolarized calcium channels, and sodium-potassium-chloride-one/potassium-chloride-two co-transporter channels as potential mechanisms utilized as tri-coordinate biomarkers with these three forms of neurologic disease at a molecular scale of electrophysiologic pathology.