Main Menu (Mobile)- Block

Main Menu - Block

custom | custom

Search Results

filters_region_cap | custom

Filter

facetapi-Q2b17qCsTdECvJIqZJgYMaGsr8vANl1n | block
facetapi-W9JlIB1X0bjs93n1Alu3wHJQTTgDCBGe | block
facetapi-61yz1V0li8B1bixrCWxdAe2aYiEXdhd0 | block
facetapi-PV5lg7xuz68EAY8eakJzrcmwtdGEnxR0 | block
general_search_page-panel_pane_1 | views_panes

55 Janelia Publications

Showing 11-20 of 55 results
Your Criteria:
    07/01/20 | Membrane potential dynamics underlying context-dependent sensory responses in the hippocampus.
    Zhao X, Wang Y, Spruston N, Magee JC
    Nature Neuroscience. 2020 Jul 1;23(7):881-91. doi: 10.1038/s41593-020-0646-2

    As animals navigate, they must identify features within context. In the mammalian brain, the hippocampus has the ability to separately encode different environmental contexts, even when they share some prominent features. To do so, neurons respond to sensory features in a context-dependent manner; however, it is not known how this encoding emerges. To examine this, we performed electrical recordings in the hippocampus as mice navigated in two distinct virtual environments. In CA1, both synaptic input to single neurons and population activity strongly tracked visual cues in one environment, whereas responses were almost completely absent when the same cue was presented in a second environment. A very similar, highly context-dependent pattern of cue-driven spiking was also observed in CA3. These results indicate that CA1 inherits a complex spatial code from upstream regions, including CA3, that have already computed a context-dependent representation of environmental features.

    View Publication Page
    04/28/20 | A Sparse, Spatially Biased Subtype of Mature Granule Cell Dominates Recruitment in Hippocampal-Associated Behaviors.
    Erwin SR, Sun W, Copeland M, Lindo S, Spruston N, Cembrowski MS
    Cell Reports. 2020 Apr 28;31(4):107551. doi: 10.1016/j.celrep.2020.107551

    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.

    View Publication Page
    02/18/20 | Transcriptional co-repressor Sin3a regulates hippocampal synaptic plasticity via Homer1/mGluR5.
    Bridi MS, Schoch H, Florian C, Poplawski SG, Banerjee A, Hawk JD, Banks GS, Lejards C, Hahn C, Giese KP, Havekes R, Spruston N, Abel T
    JCI Insight. 2020 Feb 18:. doi: 10.1172/jci.insight.92385

    Long-term memory depends on the control of activity-dependent neuronal gene expression, which is regulated by epigenetic modifications. The epigenetic modification of histones is orchestrated by the opposing activities of two classes of regulatory complexes: permissive co-activators and silencing co-repressors. Much work has focused on co-activator complexes, but little is known about the co-repressor complexes that suppress the expression of plasticity-related genes. Here, we define a critical role for the co-repressor SIN3A in memory and synaptic plasticity, showing that postnatal neuronal deletion of Sin3a enhances hippocampal long-term potentiation and long-term contextual fear memory. SIN3A regulates the expression of genes encoding proteins in the post-synaptic density. Loss of SIN3A increases expression of the synaptic scaffold Homer1, alters the mGluR1α- and mGluR5-dependence of long-term potentiation, and increases activation of extracellular signal regulated kinase (ERK) in the hippocampus after learning. Our studies define a critical role for co-repressors in modulating neural plasticity and memory consolidation and reveal that Homer1/mGluR signaling pathways may be central molecular mechanisms for memory enhancement.

    View Publication Page
    10/31/19 | ShuTu: Open-source software for efficient and accurate reconstruction of dendritic morphology.
    Jin DZ, Zhao T, Hunt DL, Tillage RP, Hsu C, Spruston N
    Frontiers in Neuroinformatics. 2019 Oct 31;13:68. doi: 10.3389/fninf.2019.00068

    Neurons perform computations by integrating inputs from thousands of synapses-mostly in the dendritic tree-to drive action potential firing in the axon. One fruitful approach to studying this process is to record from neurons using patch-clamp electrodes, fill the recorded neurons with a substance that allows subsequent staining, reconstruct the three-dimensional architectures of the dendrites, and use the resulting functional and structural data to develop computer models of dendritic integration. Accurately producing quantitative reconstructions of dendrites is typically a tedious process taking many hours of manual inspection and measurement. Here we present ShuTu, a new software package that facilitates accurate and efficient reconstruction of dendrites imaged using bright-field microscopy. The program operates in two steps: (1) automated identification of dendritic processes, and (2) manual correction of errors in the automated reconstruction. This approach allows neurons with complex dendritic morphologies to be reconstructed rapidly and efficiently, thus facilitating the use of computer models to study dendritic structure-function relationships and the computations performed by single neurons.

    View Publication Page
    Spruston LabSvoboda Lab
    10/30/19 | Functional clustering of dendritic activity during decision-making.
    Kerlin A, Boaz M, Flickinger D, MacLennan BJ, Dean MB, Davis C, Spruston N, Svoboda K
    Elife. 2019 Oct 30;8:. doi: 10.7554/eLife.46966

    The active properties of dendrites can support local nonlinear operations, but previous imaging and electrophysiological measurements have produced conflicting views regarding the prevalence and selectivity of local nonlinearities in vivo. We imaged calcium signals in pyramidal cell dendrites in the motor cortex of mice performing a tactile decision task. A custom microscope allowed us to image the soma and up to 300 μm of contiguous dendrite at 15 Hz, while resolving individual spines. New analysis methods were used to estimate the frequency and spatial scales of activity in dendritic branches and spines. The majority of dendritic calcium transients were coincident with global events. However, task-associated calcium signals in dendrites and spines were compartmentalized by dendritic branching and clustered within branches over approximately 10 μm. Diverse behavior-related signals were intermingled and distributed throughout the dendritic arbor, potentially supporting a large learning capacity in individual neurons.

    View Publication Page
    Dudman LabSternson LabSpruston LabSvoboda LabMouseLight
    09/19/19 | Reconstruction of 1,000 projection neurons reveals new cell types and organization of long-range connectivity in the mouse brain.
    Winnubst J, Bas E, Ferreira TA, Wu Z, Economo MN, Edson P, Arthur BJ, Bruns C, Rokicki K, Schauder D, Olbris DJ, Murphy SD, Ackerman DG, Arshadi C, Baldwin P, Blake R, Elsayed A, Hasan M, Ramirez D, Dos Santos B, Weldon M, Zafar A, Dudman JT, Gerfen CR, Hantman AW, Korff W, Sternson SM, Spruston N, Svoboda K, Chandrashekar J
    Cell. 2019 Sep 19;179(1):268-81. doi: 10.1016/j.cell.2019.07.042

    Neuronal cell types are the nodes of neural circuits that determine the flow of information within the brain. Neuronal morphology, especially the shape of the axonal arbor, provides an essential descriptor of cell type and reveals how individual neurons route their output across the brain. Despite the importance of morphology, few projection neurons in the mouse brain have been reconstructed in their entirety. Here we present a robust and efficient platform for imaging and reconstructing complete neuronal morphologies, including axonal arbors that span substantial portions of the brain. We used this platform to reconstruct more than 1,000 projection neurons in the motor cortex, thalamus, subiculum, and hypothalamus. Together, the reconstructed neurons constitute more than 85 meters of axonal length and are available in a searchable online database. Axonal shapes revealed previously unknown subtypes of projection neurons and suggest organizational principles of long-range connectivity.

    View Publication Page
    04/12/19 | Mapping the transcriptional diversity of genetically and anatomically defined cell populations in the mouse brain.
    Sugino K, Clark E, Schulmann A, Shima Y, Wang L, Hunt DL, Hooks BM, Traenkner D, Chandrashekar J, Picard S, Lemire AL, Spruston N, Hantman AW, Nelson SB
    Elife. 2019 Apr 12;8:. doi: 10.7554/eLife.38619

    Understanding the principles governing neuronal diversity is a fundamental goal for neuroscience. Here we provide an anatomical and transcriptomic database of nearly 200 genetically identified cell populations. By separately analyzing the robustness and pattern of expression differences across these cell populations, we identify two gene classes contributing distinctly to neuronal diversity. Short homeobox transcription factors distinguish neuronal populations combinatorially, and exhibit extremely low transcriptional noise, enabling highly robust expression differences. Long neuronal effector genes, such as channels and cell adhesion molecules, contribute disproportionately to neuronal diversity, based on their patterns rather than robustness of expression differences. By linking transcriptional identity to genetic strains and anatomical atlases we provide an extensive resource for further investigation of mouse neuronal cell types.

    View Publication Page
    04/01/19 | Multimodal in vivo brain electrophysiology with integrated glass microelectrodes.
    Hunt DL, Lai C, Smith RD, Lee AK, Harris TD, Barbic M
    Nature Biomedical Engineering. 2019 Apr 01;3(9):741-53. doi: 10.1038/s41551-019-0373-8

    Electrophysiology is the most used approach for the collection of functional data in basic and translational neuroscience, but it is typically limited to either intracellular or extracellular recordings. The integration of multiple physiological modalities for the routine acquisition of multimodal data with microelectrodes could be useful for biomedical applications, yet this has been challenging owing to incompatibilities of fabrication methods. Here, we present a suite of glass pipettes with integrated microelectrodes for the simultaneous acquisition of multimodal intracellular and extracellular information in vivo, electrochemistry assessments, and optogenetic perturbations of neural activity. We used the integrated devices to acquire multimodal signals from the CA1 region of the hippocampus in mice and rats, and show that these data can serve as ground-truth validation for the performance of spike-sorting algorithms. The microdevices are applicable for basic and translational neurobiology, and for the development of next-generation brain-machine interfaces.

    View Publication Page
    02/18/19 | Heterogeneity within classical cell types is the rule: lessons from hippocampal pyramidal neurons.
    Cembrowski MS, Spruston N
    Nature Reviews. Neuroscience. 2019 Feb 18;20(4):193-204. doi: 10.1038/s41583-019-0125-5

    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.

    View Publication Page
    10/30/18 | The subiculum is a patchwork of discrete subregions.
    Cembrowski MS, Wang L, Lemire AL, Copeland M, DiLisio SF, Clements J, Spruston N
    eLife. 2018 Oct 30;7:. doi: 10.7554/eLife.37701

    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.

    View Publication Page