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1. Perisomatic ultrastructure efficiently classifies cells in mouse cortex

   https://doi.org/10.1038/s41586-024-07765-7  

   Elabbady, Leila; Seshamani, Sharmishtaa; Mu, Shang; Mahalingam, Gayathri; Schneider-Mizell, Casey M; Bodor, Agnes L; Bae, J Alexander; Brittain, Derrick; Buchanan, JoAnn; Bumbarger, Daniel J; et al (April 2025, Nature)

   Abstract Mammalian neocortex contains a highly diverse set of cell types. These cell types have been mapped systematically using a variety of molecular, electrophysiological and morphological approaches^1–4. Each modality offers new perspectives on the variation of biological processes underlying cell-type specialization. Cellular-scale electron microscopy provides dense ultrastructural examination and an unbiased perspective on the subcellular organization of brain cells, including their synaptic connectivity and nanometre-scale morphology. In data that contain tens of thousands of neurons, most of which have incomplete reconstructions, identifying cell types becomes a clear challenge for analysis⁵. Here, to address this challenge, we present a systematic survey of the somatic region of all cells in a cubic millimetre of cortex using quantitative features obtained from electron microscopy. This analysis demonstrates that the perisomatic region is sufficient to identify cell types, including types defined primarily on the basis of their connectivity patterns. We then describe how this classification facilitates cell-type-specific connectivity characterization and locating cells with rare connectivity patterns in the dataset. 

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2. Integrating EM and Patch-seq data: Synaptic connectivity and target specificity of predicted Sst transcriptomic types

   https://doi.org/10.1101/2023.03.22.533857  

   Gamlin, CR; Schneider-Mizell, CM; Mallory, M; Elabbady, L; Gouwens, N; Williams, G; Mukora, A; Dalley, R; Bodor, A; Brittain, D; et al (March 2023, bioRxiv)

   Abstract Neural circuit function is shaped both by the cell types that comprise the circuit and the connections between those cell types¹. Neural cell types have previously been defined by morphology^{2, 3}, electrophysiology^{4, 5}, transcriptomic expression^6–8, connectivity^9–13, or even a combination of such modalities^14–16. More recently, the Patch-seq technique has enabled the characterization of morphology (M), electrophysiology (E), and transcriptomic (T) properties from individual cells^17–20. Using this technique, these properties were integrated to define 28, inhibitory multimodal, MET-types in mouse primary visual cortex²¹. It is unknown how these MET-types connect within the broader cortical circuitry however. Here we show that we can predict the MET-type identity of inhibitory cells within a large-scale electron microscopy (EM) dataset and these MET-types have distinct ultrastructural features and synapse connectivity patterns. We found that EM Martinotti cells, a well defined morphological cell type^{22, 23}known to be Somatostatin positive (Sst+)^{24, 25}, were successfully predicted to belong to Sst+ MET-types. Each identified MET-type had distinct axon myelination patterns and synapsed onto specific excitatory targets. Our results demonstrate that morphological features can be used to link cell type identities across imaging modalities, which enables further comparison of connectivity in relation to transcriptomic or electrophysiological properties. Furthermore, our results show that MET-types have distinct connectivity patterns, supporting the use of MET-types and connectivity to meaningfully define cell types. 

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3. Mechanisms Underlying Target Selectivity for Cell Types and Subcellular Domains in Developing Neocortical Circuits

   https://doi.org/10.3389/fncir.2021.728832  

   Gutman-Wei, Alan Y.; Brown, Solange P. (September 2021, Frontiers in Neural Circuits)

   The cerebral cortex contains numerous neuronal cell types, distinguished by their molecular identity as well as their electrophysiological and morphological properties. Cortical function is reliant on stereotyped patterns of synaptic connectivity and synaptic function among these neuron types, but how these patterns are established during development remains poorly understood. Selective targeting not only of different cell types but also of distinct postsynaptic neuronal domains occurs in many brain circuits and is directed by multiple mechanisms. These mechanisms include the regulation of axonal and dendritic guidance and fine-scale morphogenesis of pre- and postsynaptic processes, lineage relationships, activity dependent mechanisms and intercellular molecular determinants such as transmembrane and secreted molecules, many of which have also been implicated in neurodevelopmental disorders. However, many studies of synaptic targeting have focused on circuits in which neuronal processes target different lamina, such that cell-type-biased connectivity may be confounded with mechanisms of laminar specificity. In the cerebral cortex, each cortical layer contains cell bodies and processes from intermingled neuronal cell types, an arrangement that presents a challenge for the development of target-selective synapse formation. Here, we address progress and future directions in the study of cell-type-biased synaptic targeting in the cerebral cortex. We highlight challenges to identifying developmental mechanisms generating stereotyped patterns of intracortical connectivity, recent developments in uncovering the determinants of synaptic target selection during cortical synapse formation, and current gaps in the understanding of cortical synapse specificity. 

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4. The Synaptic Architecture of Layer 5 Thick Tufted Excitatory Neurons in the Visual Cortex of Mice

   https://doi.org/10.1101/2023.10.18.562531  

   Bodor, Agnes L; Schneider-Mizell, Casey M; Zhang, Chi; Elabbady, Leila; Mallen, Alex; Bergeson, Andi; Brittain, Derrick; Buchanan, JoAnn; Bumbarger, Daniel J; Dalley, Rachel; et al (October 2023, bioRxiv)

   Summary The neocortex is one of the most critical structures that makes us human, and it is involved in a variety of cognitive functions from perception to sensory integration and motor control. Composed of repeated modules, or microcircuits, the neocortex relies on distinct cell types as its fundamental building blocks. Despite significant progress in characterizing these cell types^1–5, an understanding of the complete synaptic partners associated with individual excitatory cell types remain elusive. Here, we investigate the connectivity of arguably the most well recognized and studied excitatory neuron in the neocortex: the thick tufted layer 5 pyramidal cell^6–10also known as extra telencephalic (ET)¹¹neurons. Although the synaptic interactions of ET neurons have been extensively explored, a comprehensive characterization of their local connectivity remains lacking. To address this knowledge gap, we leveraged a 1 mm³electron microscopic (EM) dataset. We found that ET neurons primarily establish connections with inhibitory cells in their immediate vicinity. However, when they extend their axons to other cortical regions, they tend to connect more with excitatory cells. We also find that the inhibitory cells targeted by ET neurons are a specific group of cell types, and they preferentially inhibit ET cells. Finally, we observed that the most common excitatory targets of ET neurons are layer 5 IT neurons and layer 6 pyramidal cells, whereas synapses with other ET neurons are not as common. These findings challenge current views of the connectivity of ET neurons and suggest a circuit design that involves local competition among ET neurons and collaboration with other types of excitatory cells. Our results also highlight a specific circuit pattern where a subclass of excitatory cells forms a network with specific inhibitory cell types, offering a framework for exploring the connectivity of other types of excitatory cells. 

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5. A scalable, all-optical method for mapping synaptic connectivity with cell-type specificity

   https://doi.org/10.1101/2025.06.25.661552  

   Moya, Maria V; Cunningham, William J; Vincent, Jack P; Wang, Tim; Economo, Michael N (June 2025, bioRxiv)

   ABSTRACT Single-cell transcriptomics has uncovered the enormous heterogeneity of cell types that compose each region of the mammalian brain, but describing how such diverse types connect to form functional circuits has remained challenging. Current methods for measuring the probability and strength of cell-type specific connectivity motifs principally rely on low-throughput whole-cell recording approaches. The recent development of optical tools for perturbing and observing neural circuit activity, now notably including genetically encoded voltage indicators, presents an exciting opportunity to employ optical methods to greatly increase the throughput with which circuit connectivity can be mapped physiologically. At the same time, advances in spatial transcriptomics now enable the identification of cell typesin situbased on their unique gene expression signatures. Here, we demonstrate how long-range synaptic connectivity can be assayed optically with high sensitivity, high throughput, and cell-type specificity. We apply this approach in the motor cortex to examine cell-type-specific synaptic innervation patterns of long-range thalamic and contralateral input onto more than 1000 motor cortical neurons. We find that even cell types occupying the same cortical lamina receive vastly different levels of synaptic input, a finding which was previously not possible to uncover using lower-throughput approaches that can only describe the connectivity of broad cell types. 

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