Filter
Associated Lab
- Aguilera Castrejon Lab (1) Apply Aguilera Castrejon Lab filter
- Ahrens Lab (45) Apply Ahrens Lab filter
- Aso Lab (39) Apply Aso Lab filter
- Baker Lab (19) Apply Baker Lab filter
- Betzig Lab (98) Apply Betzig Lab filter
- Beyene Lab (4) Apply Beyene Lab filter
- Bock Lab (14) Apply Bock Lab filter
- Branson Lab (45) Apply Branson Lab filter
- Card Lab (33) Apply Card Lab filter
- Cardona Lab (44) Apply Cardona Lab filter
- Chklovskii Lab (10) Apply Chklovskii Lab filter
- Clapham Lab (11) Apply Clapham Lab filter
- Cui Lab (19) Apply Cui Lab filter
- Darshan Lab (8) Apply Darshan Lab filter
- Dickson Lab (32) Apply Dickson Lab filter
- Druckmann Lab (21) Apply Druckmann Lab filter
- Dudman Lab (34) Apply Dudman Lab filter
- Eddy/Rivas Lab (30) Apply Eddy/Rivas Lab filter
- Egnor Lab (4) Apply Egnor Lab filter
- Espinosa Medina Lab (12) Apply Espinosa Medina Lab filter
- Feliciano Lab (6) Apply Feliciano Lab filter
- Fetter Lab (31) Apply Fetter Lab filter
- Fitzgerald Lab (15) Apply Fitzgerald Lab filter
- Freeman Lab (15) Apply Freeman Lab filter
- Funke Lab (34) Apply Funke Lab filter
- Gonen Lab (59) Apply Gonen Lab filter
- Grigorieff Lab (34) Apply Grigorieff Lab filter
- Harris Lab (48) Apply Harris Lab filter
- Heberlein Lab (13) Apply Heberlein Lab filter
- Hermundstad Lab (17) Apply Hermundstad Lab filter
- Hess Lab (67) Apply Hess Lab filter
- Ilanges Lab (1) Apply Ilanges Lab filter
- Jayaraman Lab (39) Apply Jayaraman Lab filter
- Ji Lab (33) Apply Ji Lab filter
- Johnson Lab (1) Apply Johnson Lab filter
- Karpova Lab (13) Apply Karpova Lab filter
- Keleman Lab (8) Apply Keleman Lab filter
- Keller Lab (60) Apply Keller Lab filter
- Lavis Lab (123) Apply Lavis Lab filter
- Lee (Albert) Lab (29) Apply Lee (Albert) Lab filter
- Leonardo Lab (19) Apply Leonardo Lab filter
- Li Lab (1) Apply Li Lab filter
- Lippincott-Schwartz Lab (88) Apply Lippincott-Schwartz Lab filter
- Liu (Zhe) Lab (53) Apply Liu (Zhe) Lab filter
- Looger Lab (136) Apply Looger Lab filter
- Magee Lab (31) Apply Magee Lab filter
- Menon Lab (12) Apply Menon Lab filter
- Murphy Lab (6) Apply Murphy Lab filter
- O'Shea Lab (3) Apply O'Shea Lab filter
- Otopalik Lab (1) Apply Otopalik Lab filter
- Pachitariu Lab (28) Apply Pachitariu Lab filter
- Pastalkova Lab (5) Apply Pastalkova Lab filter
- Pavlopoulos Lab (7) Apply Pavlopoulos Lab filter
- Pedram Lab (3) Apply Pedram Lab filter
- Podgorski Lab (16) Apply Podgorski Lab filter
- Reiser Lab (43) Apply Reiser Lab filter
- Riddiford Lab (20) Apply Riddiford Lab filter
- Romani Lab (28) Apply Romani Lab filter
- Rubin Lab (101) Apply Rubin Lab filter
- Saalfeld Lab (43) Apply Saalfeld Lab filter
- Satou Lab (1) Apply Satou Lab filter
- Scheffer Lab (36) Apply Scheffer Lab filter
- Schreiter Lab (44) Apply Schreiter Lab filter
- Shroff Lab (22) Apply Shroff Lab filter
- Simpson Lab (18) Apply Simpson Lab filter
- Singer Lab (37) Apply Singer Lab filter
- Spruston Lab (55) Apply Spruston Lab filter
- Stern Lab (69) Apply Stern Lab filter
- Sternson Lab (47) Apply Sternson Lab filter
- Stringer Lab (24) Apply Stringer Lab filter
- Svoboda Lab (131) Apply Svoboda Lab filter
- Tebo Lab (7) Apply Tebo Lab filter
- Tervo Lab (9) Apply Tervo Lab filter
- Tillberg Lab (14) Apply Tillberg Lab filter
- Tjian Lab (17) Apply Tjian Lab filter
- Truman Lab (58) Apply Truman Lab filter
- Turaga Lab (34) Apply Turaga Lab filter
- Turner Lab (24) Apply Turner Lab filter
- Vale Lab (6) Apply Vale Lab filter
- Voigts Lab (1) Apply Voigts Lab filter
- Wang (Meng) Lab (9) Apply Wang (Meng) Lab filter
- Wang (Shaohe) Lab (4) Apply Wang (Shaohe) Lab filter
- Wu Lab (8) Apply Wu Lab filter
- Zlatic Lab (26) Apply Zlatic Lab filter
- Zuker Lab (5) Apply Zuker Lab filter
Associated Project Team
- CellMap (2) Apply CellMap filter
- COSEM (3) Apply COSEM filter
- Fly Descending Interneuron (10) Apply Fly Descending Interneuron filter
- Fly Functional Connectome (14) Apply Fly Functional Connectome filter
- Fly Olympiad (5) Apply Fly Olympiad filter
- FlyEM (51) Apply FlyEM filter
- FlyLight (46) Apply FlyLight filter
- GENIE (40) Apply GENIE filter
- Integrative Imaging (1) Apply Integrative Imaging filter
- Larval Olympiad (2) Apply Larval Olympiad filter
- MouseLight (16) Apply MouseLight filter
- NeuroSeq (1) Apply NeuroSeq filter
- ThalamoSeq (1) Apply ThalamoSeq filter
- Tool Translation Team (T3) (24) Apply Tool Translation Team (T3) filter
- Transcription Imaging (45) Apply Transcription Imaging filter
Associated Support Team
- Anatomy and Histology (18) Apply Anatomy and Histology filter
- Cryo-Electron Microscopy (33) Apply Cryo-Electron Microscopy filter
- Electron Microscopy (12) Apply Electron Microscopy filter
- Fly Facility (39) Apply Fly Facility filter
- Gene Targeting and Transgenics (11) Apply Gene Targeting and Transgenics filter
- Integrative Imaging (10) Apply Integrative Imaging filter
- Janelia Experimental Technology (35) Apply Janelia Experimental Technology filter
- Management Team (1) Apply Management Team filter
- Molecular Genomics (15) Apply Molecular Genomics filter
- Primary & iPS Cell Culture (13) Apply Primary & iPS Cell Culture filter
- Project Technical Resources (35) Apply Project Technical Resources filter
- Quantitative Genomics (19) Apply Quantitative Genomics filter
- Scientific Computing Software (59) Apply Scientific Computing Software filter
- Scientific Computing Systems (6) Apply Scientific Computing Systems filter
- Viral Tools (14) Apply Viral Tools filter
- Vivarium (6) Apply Vivarium filter
Publication Date
- 2024 (128) Apply 2024 filter
- 2023 (175) Apply 2023 filter
- 2022 (166) Apply 2022 filter
- 2021 (174) Apply 2021 filter
- 2020 (177) Apply 2020 filter
- 2019 (177) Apply 2019 filter
- 2018 (206) Apply 2018 filter
- 2017 (186) Apply 2017 filter
- 2016 (191) Apply 2016 filter
- 2015 (195) Apply 2015 filter
- 2014 (190) Apply 2014 filter
- 2013 (136) Apply 2013 filter
- 2012 (112) Apply 2012 filter
- 2011 (98) Apply 2011 filter
- 2010 (61) Apply 2010 filter
- 2009 (56) Apply 2009 filter
- 2008 (40) Apply 2008 filter
- 2007 (21) Apply 2007 filter
- 2006 (3) Apply 2006 filter
2492 Janelia Publications
Showing 2381-2390 of 2492 resultsEnzymatic probes of chromatin structure reveal accessible versus inaccessible chromatin states, while super-resolution microscopy reveals a continuum of chromatin compaction states. Characterizing histone H2B movements by single-molecule tracking (SMT), we resolved chromatin domains ranging from low to high mobility and displaying different subnuclear localizations patterns. Heterochromatin constituents correlated with the lowest mobility chromatin, whereas transcription factors varied widely with regard to their respective mobility with low- or high-mobility chromatin. Pioneer transcription factors, which bind nucleosomes, can access the low-mobility chromatin domains, whereas weak or non-nucleosome binding factors are excluded from the domains and enriched in higher mobility domains. Nonspecific DNA and nucleosome binding accounted for most of the low mobility of strong nucleosome interactor FOXA1. Our analysis shows how the parameters of the mobility of chromatin-bound factors, but not their diffusion behaviors or SMT-residence times within chromatin, distinguish functional characteristics of different chromatin-interacting proteins.
This protocol provides a two-parameter analysis of single-molecule tracking (SMT) trajectories of Halo-tagged histones in living adherent cell lines and unveils a chromatin mobility landscape composed of five chromatin types, ranging from low to high mobility. When the analysis is applied to Halo-tagged, chromatin-binding proteins, it associates chromatin interaction properties with known functions in a way that previously used SMT parameters did not. For complete information on the use and execution of this protocol, please refer to Lerner et al. (2020).
Drosophila melanogaster is a model organism rich in genetic tools to manipulate and identify neural circuits involved in specific behaviors. Here we present a technique for two-photon calcium imaging in the central brain of head-fixed Drosophila walking on an air-supported ball. The ball’s motion is tracked at high resolution and can be treated as a proxy for the fly’s own movements. We used the genetically encoded calcium sensor, GCaMP3.0, to record from important elements of the motion-processing pathway, the horizontal-system lobula plate tangential cells (LPTCs) in the fly optic lobe. We presented motion stimuli to the tethered fly and found that calcium transients in horizontal-system neurons correlated with robust optomotor behavior during walking. Our technique allows both behavior and physiology in identified neurons to be monitored in a genetic model organism with an extensive repertoire of walking behaviors.
Multiphoton imaging (MPI) is widely used for recording activity simultaneously from many neurons in superficial cortical layers in vivo. We combined regenerative amplification multiphoton microscopy (RAMM) with genetically encoded calcium indicators to extend MPI of neuronal population activity into layer 5 (L5) of adult mouse somatosensory cortex. We found that this approach could be used to record and quantify spontaneous and sensory-evoked activity in populations of L5 neuronal somata located as much as 800 μm below the pia. In addition, we found that RAMM could be used to simultaneously image activity from large (80) populations of apical dendrites and follow these dendrites down to their somata of origin.
Alpha/Y-type retinal ganglion cells encode visual information with a receptive field composed of nonlinear subunits. This nonlinear subunit structure enhances sensitivity to patterns composed of high spatial frequencies. The Y-cell’s subunits are the presynaptic bipolar cells, but the mechanism for the nonlinearity remains incompletely understood. We investigated the synaptic basis of the subunit nonlinearity by combining whole-cell recording of mouse Y-type ganglion cells with two-photon fluorescence imaging of a glutamate sensor (iGluSnFR) expressed on their dendrites and throughout the inner plexiform layer. A control experiment designed to assess iGluSnFR’s dynamic range showed that fluorescence responses from Y-cell dendrites increased proportionally with simultaneously recorded excitatory current. Spatial resolution was sufficient to readily resolve independent release at intermingled ON and OFF bipolar terminals. iGluSnFR responses at Y-cell dendrites showed strong surround inhibition, reflecting receptive field properties of presynaptic release sites. Responses to spatial patterns located the origin of the Y-cell nonlinearity to the bipolar cell output, after the stage of spatial integration. The underlying mechanism differed between OFF and ON pathways: OFF synapses showed transient release and strong rectification, whereas ON synapses showed relatively sustained release and weak rectification. At ON synapses, the combination of fast release onset with slower release offset explained the nonlinear response of the postsynaptic ganglion cell. Imaging throughout the inner plexiform layer, we found transient, rectified release at the central-most levels, with increasingly sustained release near the borders. By visualizing glutamate release in real time, iGluSnFR provides a powerful tool for characterizing glutamate synapses in intact neural circuits.
We compared performance of recently developed silicon photomultipliers (SiPMs) to GaAsP photomultiplier tubes (PMTs) for two-photon imaging of neural activity. Despite higher dark counts, SiPMs match or exceed the signal-to-noise ratio of PMTs at photon rates encountered in typical calcium imaging experiments due to their low pulse height variability. At higher photon rates encountered during high-speed voltage imaging, SiPMs substantially outperform PMTs.
Recent advances in optogenetic techniques have generated new tools for controlling neuronal activity, with a wide range of neuroscience applications. The most commonly used approach has been the optical activation of the light-gated ion channel channelrhodopsin-2 (ChR2). However, targeted single-cell-level optogenetic activation with temporal precessions comparable to the spike timing remained challenging. Here we report fast (< or = 1 ms), selective, and targeted control of neuronal activity with single-cell resolution in hippocampal slices. Using temporally focused laser pulses (TEFO) for which the axial beam profile can be controlled independently of its lateral distribution, large numbers of channels on individual neurons can be excited simultaneously, leading to strong (up to 15 mV) and fast (< or = 1 ms) depolarizations. Furthermore, we demonstrated selective activation of cellular compartments, such as dendrites and large presynaptic terminals, at depths up to 150 microm. The demonstrated spatiotemporal resolution and the selectivity provided by TEFO allow manipulation of neuronal activity, with a large number of applications in studies of neuronal microcircuit function in vitro and in vivo.
External cues, including touch, enable walking animals to flexibly maneuver around obstacles and extricate themselves from dead-ends (for reviews, see [1-3]). In a screen for neurons that enable Drosophila melanogaster to retreat when it encounters a dead-end, we identified a pair of ascending neurons, the TwoLumps Ascending (TLA) neurons. Silencing TLA activity impairs backward locomotion, whereas optogenetic activation triggers backward walking. TLA-induced reversal is mediated in part by the Moonwalker Descending Neurons (MDNs) [4], which receive excitatory input from the TLAs. Silencing the TLAs decreases the extent to which freely walking flies back up upon encountering a physical barrier in the dark, and TLAs show calcium responses to optogenetic activation of neurons expressing the mechanosensory channel NOMPC. We infer that TLAs convey feedforward mechanosensory stimuli to transiently activate MDNs in response to anterior body touch.
To understand the neural basis of behavior, it is essential to sensitively and accurately measure neural activity at single neuron and single spike resolution. Extracellular electrophysiology delivers this, but it has biases in the neurons it detects and it imperfectly resolves their action potentials. To minimize these limitations, we developed a silicon probe with much smaller and denser recording sites than previous designs, called Neuropixels Ultra (NP Ultra). This device samples neuronal activity at ultra-high spatial density ( 10 times higher than previous probes) with low noise levels, while trading off recording span. NP Ultra is effectively an implantable voltage-sensing camera that captures a planar image of a neuron’s electrical field. We use a spike sorting algorithm optimized for these probes to demonstrate that the yield of visually-responsive neurons in recordings from mouse visual cortex improves up to 3-fold. We show that NP Ultra can record from small neuronal structures including axons and dendrites. Recordings across multiple brain regions and four species revealed a subset of extracellular action potentials with unexpectedly small spatial spread and axon-like features. We share a large-scale dataset of these brain-wide recordings in mice as a resource for studies of neuronal biophysics. Finally, using ground-truth identification of three major inhibitory cortical cell types, we found that these cell types were discriminable with approximately 75% success, a significant improvement over lower-resolution recordings. NP Ultra improves spike sorting performance, detection of subcellular compartments, and cell type classification to enable more powerful dissection of neural circuit activity during behavior.
To study the neural basis of behavior, we require methods to sensitively and accurately measure neural activity at single neuron and single spike resolution. Extracellular electrophysiology is a principal method for achieving this, but it has biases in the neurons it detects and it imperfectly resolves their action potentials. To overcome these limitations, we developed a silicon probe with significantly smaller and denser recording sites than previous designs, called Neuropixels Ultra (NP Ultra). This device measures neuronal activity at ultra-high densities (>1300 sites per mm, 10 times higher than previous probes), with 6 µm center-to-center spacing and low noise. This device effectively comprises an implantable voltage-sensing camera that captures a planar image of a neuron's electrical field. We introduce a new spike sorting algorithm optimized for these probes and use it to find that the yield of visually-responsive neurons in recordings from mouse visual cortex improves ∼3-fold. Recordings across multiple brain regions and four species revealed a subset of unexpectedly small extracellular action potentials not previously reported. Further experiments determined that, in visual cortex, these do not correspond to major subclasses of interneurons and instead likely reflect recordings from axons. Finally, using ground-truth identification of cortical inhibitory cell types with optotagging, we found that cell type was discriminable with approximately 75% success among three types, a significant improvement over lower-resolution recordings. NP Ultra improves spike sorting performance, sampling bias, and cell type classification.