Main Menu (Mobile)- Block

Main Menu - Block

custom | custom

Search Results

filters_region_cap | custom

Filter

facetapi-Q2b17qCsTdECvJIqZJgYMaGsr8vANl1n | block
facetapi-W9JlIB1X0bjs93n1Alu3wHJQTTgDCBGe | block

Associated Project Team

facetapi-61yz1V0li8B1bixrCWxdAe2aYiEXdhd0 | block

Associated Support Team

facetapi-PV5lg7xuz68EAY8eakJzrcmwtdGEnxR0 | block
facetapi-aK0bSsPXQOqhYQEgonL2xGNrv4SPvFLb | block

Tool Types

general_search_page-panel_pane_1 | views_panes

5 Janelia Publications

Showing 1-5 of 5 results
Your Criteria:
    03/11/09 | Loss of sensitivity in an analog neural circuit.
    Borghuis BG, Sterling P, Smith RG
    The Journal of Neuroscience: The Official Journal of the Society for Neuroscience. 2009 Mar 11;29:3045-58. doi: 10.1523/JNEUROSCI.5071-08.2009

    A low-contrast spot that activates just one ganglion cell in the retina is detected in the spike train of the cell with about the same sensitivity as it is detected behaviorally. This is consistent with Barlow’s proposal that the ganglion cell and later stages of spiking neurons transfer information essentially without loss. Yet, when losses of sensitivity by all preneural factors are accounted for, predicted sensitivity near threshold is considerably greater than behavioral sensitivity, implying that somewhere in the brain information is lost. We hypothesized that the losses occur mainly in the retina, where graded signals are processed by analog circuits that transfer information at high rates and low metabolic cost. To test this, we constructed a model that included all preneural losses for an in vitro mammalian retina, and evaluated the model to predict sensitivity at the cone output. Recording graded responses postsynaptic to the cones (from the type A horizontal cell) and comparing to predicted preneural sensitivity, we found substantial loss of sensitivity (4.2-fold) across the first visual synapse. Recording spike responses from brisk-transient ganglion cells stimulated with the same spot, we found a similar loss (3.5-fold) across the second synapse. The total retinal loss approximated the known overall loss, supporting the hypothesis that from stimulus to perception, most loss near threshold is retinal.

    View Publication Page
    03/06/09 | Crystal structures of the GCaMP calcium sensor reveal the mechanism of fluorescence signal change and aid rational design.
    Akerboom J, Rivera JD, Guilbe MM, Malavé EC, Hernandez HH, Tian L, Hires SA, Marvin JS, Looger LL, Schreiter ER
    The Journal of Biological Chemistry. 2009 Mar 6;284:6455-64. doi: 10.1074/jbc.M807657200

    The genetically encoded calcium indicator GCaMP2 shows promise for neural network activity imaging, but is currently limited by low signal-to-noise ratio. We describe x-ray crystal structures as well as solution biophysical and spectroscopic characterization of GCaMP2 in the calcium-free dark state, and in two calcium-bound bright states: a monomeric form that dominates at intracellular concentrations observed during imaging experiments and an unexpected domain-swapped dimer with decreased fluorescence. This series of structures provides insight into the mechanism of Ca2+-induced fluorescence change. Upon calcium binding, the calmodulin (CaM) domain wraps around the M13 peptide, creating a new domain interface between CaM and the circularly permuted enhanced green fluorescent protein domain. Residues from CaM alter the chemical environment of the circularly permuted enhanced green fluorescent protein chromophore and, together with flexible inter-domain linkers, block solvent access to the chromophore. Guided by the crystal structures, we engineered a series of GCaMP2 point mutants to probe the mechanism of GCaMP2 function and characterized one mutant with significantly improved signal-to-noise. The mutation is located at a domain interface and its effect on sensor function could not have been predicted in the absence of structural data.

    View Publication Page
    Hess LabFetter Lab
    03/03/09 | Interferometric fluorescent super-resolution microscopy resolves 3D cellular ultrastructure.
    Shtengel G, Galbraith JA, Galbraith CG, Lippincott-Schwartz J, Gillette JM, Manley S, Sougrat R, Waterman CM, Kanchanawong P, Davidson MW, Fetter RD, Hess HF
    Proceedings of the National Academy of Sciences of the United States of America. 2009 Mar 3;106:3125-30. doi: 10.1073/pnas.0813131106

    Understanding molecular-scale architecture of cells requires determination of 3D locations of specific proteins with accuracy matching their nanometer-length scale. Existing electron and light microscopy techniques are limited either in molecular specificity or resolution. Here, we introduce interferometric photoactivated localization microscopy (iPALM), the combination of photoactivated localization microscopy with single-photon, simultaneous multiphase interferometry that provides sub-20-nm 3D protein localization with optimal molecular specificity. We demonstrate measurement of the 25-nm microtubule diameter, resolve the dorsal and ventral plasma membranes, and visualize the arrangement of integrin receptors within endoplasmic reticulum and adhesion complexes, 3D protein organization previously resolved only by electron microscopy. iPALM thus closes the gap between electron tomography and light microscopy, enabling both molecular specification and resolution of cellular nanoarchitecture.

    View Publication Page
    03/01/09 | A proposal for a coordinated effort for the determination of brainwide neuroanatomical connectivity in model organisms at a mesoscopic scale.
    Bohland JW, Wu C, Barbas H, Bokil H, Bota M, Breiter HC, Cline HT, Doyle JC, Freed PJ, Greenspan RJ, Haber SN, Hawrylycz M, Herrera DG, Hilgetag CC, Huang ZJ, Jones A, Jones EG, Karten HJ, Kleinfeld D, Kötter R, Lester HA, Lin JM, Mensh BD, Mikula S, Panksepp J, Price JL, Safdieh J, Saper CB, Schiff ND, Schmahmann JD, Stillman BW, Svoboda K, Swanson LW, Toga AW, Van Essen DC, Watson JD, Mitra PP
    PLoS Computational Biology. 2009 Mar;5(3):e1000334. doi: 10.1371/journal.pcbi.1000334

    In this era of complete genomes, our knowledge of neuroanatomical circuitry remains surprisingly sparse. Such knowledge is critical, however, for both basic and clinical research into brain function. Here we advocate for a concerted effort to fill this gap, through systematic, experimental mapping of neural circuits at a mesoscopic scale of resolution suitable for comprehensive, brainwide coverage, using injections of tracers or viral vectors. We detail the scientific and medical rationale and briefly review existing knowledge and experimental techniques. We define a set of desiderata, including brainwide coverage; validated and extensible experimental techniques suitable for standardization and automation; centralized, open-access data repository; compatibility with existing resources; and tractability with current informatics technology. We discuss a hypothetical but tractable plan for mouse, additional efforts for the macaque, and technique development for human. We estimate that the mouse connectivity project could be completed within five years with a comparatively modest budget.

    View Publication Page
    03/01/09 | VANO: a volume-object image annotation system.
    Peng H, Long F, Myers EW
    Bioinformatics. 2009 Mar 1;25:695-7. doi: 10.1093/bioinformatics/btp046

    Volume-object annotation system (VANO) is a cross-platform image annotation system that enables one to conveniently visualize and annotate 3D volume objects including nuclei and cells. An application of VANO typically starts with an initial collection of objects produced by a segmentation computation. The objects can then be labeled, categorized, deleted, added, split, merged and redefined. VANO has been used to build high-resolution digital atlases of the nuclei of Caenorhabditis elegans at the L1 stage and the nuclei of Drosophila melanogaster’s ventral nerve cord at the late embryonic stage. AVAILABILITY: Platform independent executables of VANO, a sample dataset, and a detailed description of both its design and usage are available at research.janelia.org/peng/proj/vano. VANO is open-source for co-development.

    View Publication Page