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06/05/18 | Persistent sodium current mediates the steep voltage dependence of spatial coding in hippocampal pyramidal neurons.
Hsu CL, Zhao X, Milstein AD, Spruston N
Neuron. 2018 Jun 05:. doi: 10.1016/j.neuron.2018.05.025

The mammalian hippocampus forms a cognitive map using neurons that fire according to an animal's position ("place cells") and many other behavioral and cognitive variables. The responses of these neurons are shaped by their presynaptic inputs and the nature of their postsynaptic integration. In CA1 pyramidal neurons, spatial responses in vivo exhibit a strikingly supralinear dependence on baseline membrane potential. The biophysical mechanisms underlying this nonlinear cellular computation are unknown. Here, through a combination of in vitro, in vivo, and in silico approaches, we show that persistent sodium current mediates the strong membrane potential dependence of place cell activity. This current operates at membrane potentials below the action potential threshold and over seconds-long timescales, mediating a powerful and rapidly reversible amplification of synaptic responses, which drives place cell firing. Thus, we identify a biophysical mechanism that shapes the coding properties of neurons composing the hippocampal cognitive map.

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06/18/18 | A novel pyramidal cell type promotes sharp-wave synchronization in the hippocampus.
Hunt DL, Linaro D, Si B, Romani S, Spruston N
Nature Neuroscience. 2018 Jun 18:. doi: 10.1038/s41593-018-0172-7

To support cognitive function, the CA3 region of the hippocampus performs computations involving attractor dynamics. Understanding how cellular and ensemble activities of CA3 neurons enable computation is critical for elucidating the neural correlates of cognition. Here we show that CA3 comprises not only classically described pyramid cells with thorny excrescences, but also includes previously unidentified 'athorny' pyramid cells that lack mossy-fiber input. Moreover, the two neuron types have distinct morphological and physiological phenotypes and are differentially modulated by acetylcholine. To understand the contribution of these athorny pyramid neurons to circuit function, we measured cell-type-specific firing patterns during sharp-wave synchronization events in vivo and recapitulated these dynamics with an attractor network model comprising two principal cell types. Our data and simulations reveal a key role for athorny cell bursting in the initiation of sharp waves: transient network attractor states that signify the execution of pattern completion computations vital to cognitive function.

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02/19/18 | Single excitatory axons form clustered synapses onto CA1 pyramidal cell dendrites
Bloss EB, Cembrowski MS, Karsh B, Colonell J, Fetter RD, Spruston N
Nature Neuroscience. 2018 Mar;21(3):353-63. doi: 10.1038/s41593-018-0084-6

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.

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05/17/17 | Integrating Results across Methodologies Is Essential for Producing Robust Neuronal Taxonomies.
Cembrowski MS, Spruston N
Neuron. 2017 May 17;94(4):747-751.e1. doi: 10.1016/j.neuron.2017.04.023

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.

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04/26/16 | Hipposeq: a comprehensive RNA-seq database of gene expression in hippocampal principal neurons.
Cembrowski MS, Wang L, Sugino K, Shields BC, Spruston N
eLife. 2016;5:. doi: 10.7554/eLife.14997

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.

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02/18/16 | Structured Dendritic Inhibition Supports Branch-Selective Integration in CA1 Pyramidal Cells.
Bloss EB, Cembrowski MS, Karsh B, Colonell J, Fetter RD, Spruston N
Neuron. 2016 Feb 18:. doi: 10.1016/j.neuron.2016.01.029

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.

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01/20/16 | Spatial Gene-Expression Gradients Underlie Prominent Heterogeneity of CA1 Pyramidal Neurons.
Cembrowski MS, Bachman JL, Wang L, Sugino K, Shields BC, Spruston N
Neuron. 2016 Jan 13:. doi: 10.1016/j.neuron.2015.12.013

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 population-hippocampal 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.

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11/26/15 | Dendritic integration: 60 years of progress.
Stuart GJ, Spruston N
Nature Neuroscience. 2015 Dec;18(12):1713-21. doi: 10.1038/nn.4157

Understanding how individual neurons integrate the thousands of synaptic inputs they receive is critical to understanding how the brain works. Modeling studies in silico and experimental work in vitro, dating back more than half a century, have revealed that neurons can perform a variety of different passive and active forms of synaptic integration on their inputs. But how are synaptic inputs integrated in the intact brain? With the development of new techniques, this question has recently received substantial attention, with new findings suggesting that many of the forms of synaptic integration observed in vitro also occur in vivo, including in awake animals. Here we review six decades of progress, which collectively highlights the complex ways that single neurons integrate their inputs, emphasizing the critical role of dendrites in information processing in the brain.

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