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56 Janelia Publications

Showing 21-30 of 56 results
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    Magee Lab
    10/16/09 | Fast synaptic subcortical control of hippocampal circuits.
    Varga V, Losonczy A, Zemelman BV, Borhegyi Z, Nyiri G, Domonkos A, Hangya B, Holderith N, Magee JC, Freund TF
    Science. 2009 Oct 16;326(5951):449-53. doi: 10.1126/science.1178307

    Cortical information processing is under state-dependent control of subcortical neuromodulatory systems. Although this modulatory effect is thought to be mediated mainly by slow nonsynaptic metabotropic receptors, other mechanisms, such as direct synaptic transmission, are possible. Yet, it is currently unknown if any such form of subcortical control exists. Here, we present direct evidence of a strong, spatiotemporally precise excitatory input from an ascending neuromodulatory center. Selective stimulation of serotonergic median raphe neurons produced a rapid activation of hippocampal interneurons. At the network level, this subcortical drive was manifested as a pattern of effective disynaptic GABAergic inhibition that spread throughout the circuit. This form of subcortical network regulation should be incorporated into current concepts of normal and pathological cortical function.

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    07/26/09 | Fast throughput low voltage scanning transmission electron microscope imaging of nano-resolution three dimensional tissue.
    Bolorizadeh M, Hess HF
    Microscopy and Microanalysis. 2009 Jul 26;15:642-3. doi: 10.1017/S1431927609092435
    01/01/09 | Imaging informatics for personalised medicine: applications and challenges.
    Liu T, Peng H, Zhou X
    International Journal of Functional Informatics and Personalised Medicine. 2009;2(2):125-35. doi: 10.1007/s12021-010-9090-x

    Imaging informatics has emerged as a major research theme in biomedicine in the last few decades. Currently, personalised, predictive and preventive patient care is believed to be one of the top priorities in biomedical research and practice. Imaging informatics plays a major role in biomedicine studies. This paper reviews main applications and challenges of imaging informatics in biomedicine.

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    Looger LabSvoboda LabJayaraman LabSchreiter Lab
    12/01/09 | Imaging neural activity in worms, flies and mice with improved GCaMP calcium indicators.
    Tian L, Hires SA, Mao T, Huber D, Chiappe ME, Chalasani SH, Petreanu L, Akerboom J, McKinney SA, Schreiter ER, Bargmann CI, Jayaraman V, Svoboda K, Looger LL
    Nature Methods. 2009 Dec;6(12):875-81. doi: 10.1038/nmeth.1398

    Genetically encoded calcium indicators (GECIs) can be used to image activity in defined neuronal populations. However, current GECIs produce inferior signals compared to synthetic indicators and recording electrodes, precluding detection of low firing rates. We developed a single-wavelength GCaMP2-based GECI (GCaMP3), with increased baseline fluorescence (3-fold), increased dynamic range (3-fold) and higher affinity for calcium (1.3-fold). We detected GCaMP3 fluorescence changes triggered by single action potentials in pyramidal cell dendrites, with signal-to-noise ratio and photostability substantially better than those of GCaMP2, D3cpVenus and TN-XXL. In Caenorhabditis elegans chemosensory neurons and the Drosophila melanogaster antennal lobe, sensory stimulation-evoked fluorescence responses were significantly enhanced with GCaMP3 (4-6-fold). In somatosensory and motor cortical neurons in the intact mouse, GCaMP3 detected calcium transients with amplitudes linearly dependent on action potential number. Long-term imaging in the motor cortex of behaving mice revealed large fluorescence changes in imaged neurons over months.

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    Eddy/Rivas Lab
    05/15/09 | Infernal 1.0: inference of RNA alignments.
    Nawrocki EP, Kolbe DL, Eddy SR
    Bioinformatics. 2009 May 15;25:1335-7. doi: 10.1093/bioinformatics/btp157

    SUMMARY: INFERNAL builds consensus RNA secondary structure profiles called covariance models (CMs), and uses them to search nucleic acid sequence databases for homologous RNAs, or to create new sequence- and structure-based multiple sequence alignments. AVAILABILITY: Source code, documentation and benchmark downloadable from http://infernal.janelia.org. INFERNAL is freely licensed under the GNU GPLv3 and should be portable to any POSIX-compliant operating system, including Linux and Mac OS/X.

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    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.

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    09/30/09 | Lessons from a compartmental model of a Drosophila neuron.
    Tuthill JC
    The Journal of Neuroscience: The Official Journal of the Society for Neuroscience. 2009 Sep 30;29(39):12033-4. doi: 10.1523/JNEUROSCI.3348-09.2009

    Although the vinegar fly, Drosophila melanogaster, has been a biological model organism for over a century, its emergence as a model system for the study of neurophysiology is comparatively recent. The primary reason for this is that the vinegar fly and its neurons are tiny; up until 5 years ago, it was prohibitively difficult to record intracellularly from individual neurons in the intact Drosophila brain (Wilson et al., 2004). Today, fly electrophysiologists can genetically label neurons with GFP and reliably record from many (but not all) neurons in the fruit fly brain. Using genetic tools to drive expression of fluorescent calcium indicators, light-sensitive ion channels, or cell activity suppressors, we are beginning to understand how the external environment is represented with electrical potentials in Drosophila neurons (for review, see Olsen and Wilson, 2008).

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    Eddy/Rivas Lab
    05/15/09 | Local RNA structure alignment with incomplete sequence.
    Kolbe DL, Eddy SR
    Bioinformatics. 2009 May 15;25(10):1236-43. doi: 10.1093/bioinformatics/btp154

    Accuracy of automated structural RNA alignment is improved by using models that consider not only primary sequence but also secondary structure information. However, current RNA structural alignment approaches tend to perform poorly on incomplete sequence fragments, such as single reads from metagenomic environmental surveys, because nucleotides that are expected to be base paired are missing.

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    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.

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    Simpson Lab
    01/01/09 | Mapping and manipulating neural circuits in the fly brain.
    Simpson JH
    Advances in Genetics. 2009;65:79-143. doi: 10.1016/S0065-2660(09)65003-3

    Drosophila is a marvelous system to study the underlying principles that govern how neural circuits govern behaviors. The scale of the fly brain (approximately 100,000 neurons) and the complexity of the behaviors the fly can perform make it a tractable experimental model organism. In addition, 100 years and hundreds of labs have contributed to an extensive array of tools and techniques that can be used to dissect the function and organization of the fly nervous system. This review discusses both the conceptual challenges and the specific tools for a neurogenetic approach to circuit mapping in Drosophila.

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