Filter
Associated Lab
- Aguilera Castrejon Lab (1) Apply Aguilera Castrejon Lab filter
- Ahrens Lab (47) Apply Ahrens Lab filter
- Aso Lab (39) Apply Aso Lab filter
- Baker Lab (19) Apply Baker Lab filter
- Betzig Lab (99) Apply Betzig Lab filter
- Beyene Lab (8) Apply Beyene Lab filter
- Bock Lab (14) Apply Bock Lab filter
- Branson Lab (45) Apply Branson Lab filter
- Card Lab (34) Apply Card Lab filter
- Cardona Lab (44) Apply Cardona Lab filter
- Chklovskii Lab (10) Apply Chklovskii Lab filter
- Clapham Lab (12) 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 (36) Apply Funke Lab filter
- Gonen Lab (59) Apply Gonen Lab filter
- Grigorieff Lab (34) Apply Grigorieff Lab filter
- Harris Lab (49) Apply Harris Lab filter
- Heberlein Lab (13) Apply Heberlein Lab filter
- Hermundstad Lab (20) Apply Hermundstad Lab filter
- Hess Lab (70) Apply Hess Lab filter
- Ilanges Lab (1) Apply Ilanges Lab filter
- Jayaraman Lab (41) 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 (61) Apply Keller Lab filter
- Koay Lab (1) Apply Koay Lab filter
- Lavis Lab (128) Apply Lavis Lab filter
- Lee (Albert) Lab (29) Apply Lee (Albert) Lab filter
- Leonardo Lab (19) Apply Leonardo Lab filter
- Li Lab (3) Apply Li Lab filter
- Lippincott-Schwartz Lab (89) Apply Lippincott-Schwartz Lab filter
- Liu (Zhe) Lab (56) 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 (5) Apply O'Shea Lab filter
- Otopalik Lab (1) Apply Otopalik Lab filter
- Pachitariu Lab (31) 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 (44) Apply Reiser Lab filter
- Riddiford Lab (20) Apply Riddiford Lab filter
- Romani Lab (30) Apply Romani Lab filter
- Rubin Lab (102) Apply Rubin Lab filter
- Saalfeld Lab (44) Apply Saalfeld Lab filter
- Satou Lab (1) Apply Satou Lab filter
- Scheffer Lab (36) Apply Scheffer Lab filter
- Schreiter Lab (47) Apply Schreiter Lab filter
- Shroff Lab (24) 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 (70) Apply Stern Lab filter
- Sternson Lab (47) Apply Sternson Lab filter
- Stringer Lab (27) 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 (25) Apply Turner Lab filter
- Vale Lab (7) Apply Vale Lab filter
- Voigts Lab (2) Apply Voigts Lab filter
- Wang (Meng) Lab (13) Apply Wang (Meng) Lab filter
- Wang (Shaohe) Lab (5) 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 (8) Apply CellMap filter
- COSEM (3) Apply COSEM filter
- FIB-SEM Technology (1) Apply FIB-SEM Technology 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 (52) Apply FlyEM filter
- FlyLight (47) 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) (26) Apply Tool Translation Team (T3) filter
- Transcription Imaging (45) Apply Transcription Imaging filter
Associated Support Team
- Project Pipeline Support (2) Apply Project Pipeline Support filter
- Anatomy and Histology (18) Apply Anatomy and Histology filter
- Cryo-Electron Microscopy (33) Apply Cryo-Electron Microscopy filter
- Electron Microscopy (14) Apply Electron Microscopy filter
- Gene Targeting and Transgenics (11) Apply Gene Targeting and Transgenics filter
- Integrative Imaging (14) Apply Integrative Imaging filter
- Invertebrate Shared Resource (39) Apply Invertebrate Shared Resource 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 (14) Apply Primary & iPS Cell Culture filter
- Project Technical Resources (40) Apply Project Technical Resources filter
- Quantitative Genomics (19) Apply Quantitative Genomics filter
- Scientific Computing Software (65) 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 (207) Apply 2024 filter
- 2023 (163) 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
2559 Janelia Publications
Showing 151-160 of 2559 resultsAnimals are often bombarded with visual information and must prioritize specific visual features based on their current needs. The neuronal circuits that detect and relay visual features have been well-studied. Yet, much less is known about how an animal adjusts its visual attention as its goals or environmental conditions change. During social behaviors, flies need to focus on nearby flies. Here, we study how the flow of visual information is altered when female Drosophila enter an aggressive state. From the connectome, we identified three state-dependent circuit motifs poised to selectively amplify the response of an aggressive female to fly-sized visual objects: convergence of excitatory inputs from neurons conveying select visual features and internal state; dendritic disinhibition of select visual feature detectors; and a switch that toggles between two visual feature detectors. Using cell-type-specific genetic tools, together with behavioral and neurophysiological analyses, we show that each of these circuit motifs function during female aggression. We reveal that features of this same switch operate in males during courtship pursuit, suggesting that disparate social behaviors may share circuit mechanisms. Our work provides a compelling example of using the connectome to infer circuit mechanisms that underlie dynamic processing of sensory signals.Competing Interest StatementThe authors have declared no competing interest.
Eukaryotic gene expression is linked to chromatin structure and nucleosome positioning by ATP-dependent chromatin remodelers that establish and maintain nucleosome-depleted regions (NDRs) near transcription start sites. Conserved yeast RSC and ISW2 remodelers exert antagonistic effects on nucleosomes flanking NDRs, but the temporal dynamics of remodeler search, engagement, and directional nucleosome mobilization for promoter accessibility are unknown. Using optical tweezers and two-color single-particle imaging, we investigated the Brownian diffusion of RSC and ISW2 on free DNA and sparse nucleosome arrays. RSC and ISW2 rapidly scan DNA by one-dimensional hopping and sliding, respectively, with dynamic collisions between remodelers followed by recoil or apparent co-diffusion. Static nucleosomes block remodeler diffusion resulting in remodeler recoil or sequestration. Remarkably, both RSC and ISW2 use ATP hydrolysis to translocate mono-nucleosomes processively at ~30 bp/s on extended linear DNA under tension. Processivity and opposing push-pull directionalities of nucleosome translocation shown by RSC and ISW2 shape the distinctive landscape of promoter chromatin.
Fluorescent carbon nanomaterials have broadly useful chemical and photophysical attributes that are conducive to applications in biology. In this review, we focus on materials whose photophysics allow for the use of these materials in biomedical and environmental applications, with emphasis on imaging, biosensing, and cargo delivery. The review focuses primarily on graphitic carbon nanomaterials including graphene and its derivatives, carbon nanotubes, as well as carbon dots and carbon nanohoops. Recent advances in and future prospects of these fields are discussed at depth, and where appropriate, references to reviews pertaining to older literature are provided.
Neuroscience research in Drosophila is benefiting from large-scale connectomics efforts using electron microscopy (EM) to reveal all the neurons in a brain and their connections. To exploit this knowledge base, researchers relate a connectome’s structure to neuronal function, often by studying individual neuron cell types. Vast libraries of fly driver lines expressing fluorescent reporter genes in sets of neurons have been created and imaged using confocal light microscopy (LM), enabling the targeting of neurons for experimentation. However, creating a fly line for driving gene expression within a single neuron found in an EM connectome remains a challenge, as it typically requires identifying a pair of driver lines where only the neuron of interest is expressed in both. This task and other emerging scientific workflows require finding similar neurons across large data sets imaged using different modalities. Here, we present NeuronBridge, a web application for easily and rapidly finding putative morphological matches between large data sets of neurons imaged using different modalities. We describe the functionality and construction of the NeuronBridge service, including its user-friendly graphical user interface (GUI), extensible data model, serverless cloud architecture, and massively parallel image search engine. NeuronBridge fills a critical gap in the Drosophila research workflow and is used by hundreds of neuroscience researchers around the world. We offer our software code, open APIs, and processed data sets for integration and reuse, and provide the application as a service at http://neuronbridge.janelia.org.Background
Results
Conclusions
The body of an animal determines how the nervous system produces behavior. Therefore, detailed modeling of the neural control of sensorimotor behavior requires a detailed model of the body. Here we contribute an anatomically-detailed biomechanical whole-body model of the fruit fly Drosophila melanogaster in the MuJoCo physics engine. Our model is general-purpose, enabling the simulation of diverse fly behaviors, both on land and in the air. We demonstrate the generality of our model by simulating realistic locomotion, both flight and walking. To support these behaviors, we have extended MuJoCo with phenomenological models of fluid forces and adhesion forces. Through data-driven end-to-end reinforcement learning, we demonstrate that these advances enable the training of neural network controllers capable of realistic locomotion along complex trajectories based on high-level steering control signals. With a visually guided flight task, we demonstrate a neural controller that can use the vision sensors of the body model to control and steer flight. Our project is an open-source platform for modeling neural control of sensorimotor behavior in an embodied context.Competing Interest StatementThe authors have declared no competing interest.
Chromosome inversions are of unique importance in the evolution of genomes and species because when heterozygous with a standard arrangement chromosome, they suppress meiotic crossovers within the inversion. In Drosophila species, heterozygous inversions also cause the interchromosomal effect, whereby the presence of a heterozygous inversion induces a dramatic increase in crossover frequencies in the remainder of the genome within a single meiosis. To date, the interchromosomal effect has been studied exclusively in species that also have high frequencies of inversions in wild populations. We took advantage of a recently developed approach for generating inversions in Drosophila simulans, a species that does not have inversions in wild populations, to ask if there is an interchromosomal effect. We used the existing chromosome 3R balancer and generated a new chromosome 2L balancer to assay for the interchromosomal effect genetically and cytologically. We found no evidence of an interchromosomal effect in D. simulans. To gain insight into the underlying mechanistic reasons, we qualitatively analyzed the relationship between meiotic double-strand break formation and synaptonemal complex assembly. We find that the synaptonemal complex is assembled prior to double-strand break formation as in D. melanogaster; however, we show that the synaptonemal complex is assembled prior to localization of the oocyte determination factor Orb, whereas in D. melanogaster, synaptonemal complex formation does not begin until Orb is localized. Together, our data show heterozygous inversions in D. simulans do not induce an interchromosomal effect and that there are differences in the developmental programming of the early stages of meiosis.
The sense of direction is critical for survival in changing environments and relies on flexibly integrating self-motion signals with external sensory cues. While the anatomical substrates involved in head direction (HD) coding are well known, the mechanisms by which visual information updates HD representations remain poorly understood. Retrosplenial cortex (RSC) plays a key role in forming coherent representations of space in mammals and it encodes a variety of navigational variables, including HD. Here, we use simultaneous two-area tetrode recording to show that RSC HD representation is nearly synchronous with that of the anterodorsal nucleus of thalamus (ADn), the obligatory thalamic relay of HD to cortex, during rotation of a prominent visual cue. Moreover, coordination of HD representations in the two regions is maintained during darkness. We further show that anatomical and functional connectivity are consistent with a strong feedforward drive of HD information from ADn to RSC, with anatomically restricted corticothalamic feedback. Together, our results indicate a concerted global HD reference update across cortex and thalamus.
Signaling by the Ral small GTPase is poorly understood . animals with constitutively activated RAL-1 or deficient for the inhibitory RalGAP, HGAP-1 /2, display pale intestines. Staining with Oil Red O detected decreased intestinal lipids in the deletion mutant relative to the wild type. Constitutively activated RAL-1 decreased lipid detected by stimulated Raman scattering (SRS) microscopy, a label-free method of detecting lipid by laser excitation and detection. A signaling-deficient missense mutant for RAL-1 also displayed reduced lipid staining via SRS. We conclude that RAL-1 signaling regulates lipid homeostasis, biosynthesis or storage in live animals.
Dendritic spines are tiny protrusions found along the dendrites of neurons, and their number is a measure of the density of synaptic connections. Altered density and morphology is observed in several pathologies, and spine formation as well as morphological changes correlate with learning and memory. The detection of spines in microscopy images and the analysis of their morphology is therefore a prerequisite for many studies. We have developed a new open-source, freely available, plugin for ImageJ/FIJI, called Spot Spine, that allows detection and morphological measurements of spines in three dimensional images. Local maxima are detected in spine heads, and the intensity distribution around the local maximum is computed to perform the segmentation of each spine head. Spine necks are then traced from the spine head to the dendrite. Several parameters can be set to optimize detection and segmentation, and manual correction gives further control over the result of the process. The plugin allows the analysis of images of dendrites obtained with various labeling and imaging methods. Quantitative measurements are retrieved including spine head volume and surface, and neck length. The plugin and instructions for use are available at https://imagej.net/plugins/spot-spine.Background
Method
Results
Conclusion
Polarized fluorescence microscopy is a valuable tool for measuring molecular orientations, but techniques for recovering three-dimensional orientations and positions of fluorescent ensembles are limited. We report a polarized dual-view light-sheet system for determining the three-dimensional orientations and diffraction-limited positions of ensembles of fluorescent dipoles that label biological structures, and we share a set of visualization, histogram, and profiling tools for interpreting these positions and orientations. We model our samples, their excitation, and their detection using coarse-grained representations we call orientation distribution functions (ODFs). We apply ODFs to create physics-informed models of image formation with spatio-angular point-spread and transfer functions. We use theory and experiment to conclude that light-sheet tilting is a necessary part of our design for recovering all three-dimensional orientations. We use our system to extend known two-dimensional results to three dimensions in FM1-43-labelled giant unilamellar vesicles, fast-scarlet-labelled cellulose in xylem cells, and phalloidin-labelled actin in U2OS cells. Additionally, we observe phalloidin-labelled actin in mouse fibroblasts grown on grids of labelled nanowires and identify correlations between local actin alignment and global cell-scale orientation, indicating cellular coordination across length scales.Competing Interest StatementH.S., A.K., S.M., P.L.R., R.O., Y.W., and T.C. hold US Patent #11428632.