Filter
Associated Lab
- Aguilera Castrejon Lab (1) Apply Aguilera Castrejon Lab filter
- Ahrens Lab (46) 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 (5) 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 (35) 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 (18) Apply Hermundstad Lab filter
- Hess Lab (69) Apply Hess Lab filter
- Ilanges Lab (1) Apply Ilanges Lab filter
- Jayaraman Lab (40) 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
- Koay Lab (1) Apply Koay Lab filter
- Lavis Lab (126) 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 (30) 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 (29) Apply Romani Lab filter
- Rubin Lab (101) 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 (45) 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 (69) Apply Stern Lab filter
- Sternson Lab (47) Apply Sternson Lab filter
- Stringer Lab (26) 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 (2) Apply Voigts Lab filter
- Wang (Meng) Lab (10) 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 (6) 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
- Project Pipeline Support (1) 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 (13) Apply Electron Microscopy filter
- Gene Targeting and Transgenics (11) Apply Gene Targeting and Transgenics filter
- Integrative Imaging (13) 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 (13) Apply Primary & iPS Cell Culture filter
- Project Technical Resources (37) Apply Project Technical Resources filter
- Quantitative Genomics (19) Apply Quantitative Genomics filter
- Scientific Computing Software (63) 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 (170) Apply 2024 filter
- 2023 (170) 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
2529 Janelia Publications
Showing 241-250 of 2529 resultsCytotoxic T lymphocytes (CTLs) use polarized secretion to rapidly destroy virally infected and tumor cells. To understand the temporal relationships between key events leading to secretion, we used high-resolution 4D imaging. CTLs approached targets with actin-rich projections at the leading edge, creating an initially actin-enriched contact with rearward-flowing actin. Within 1 min, cortical actin reduced across the synapse, T cell receptors (TCRs) clustered centrally to form the central supramolecular activation cluster (cSMAC), and centrosome polarization began. Granules clustered around the moving centrosome within 2.5 min and reached the synapse after 6 min. TCR-bearing intracellular vesicles were delivered to the cSMAC as the centrosome docked. We found that the centrosome and granules were delivered to an area of membrane with reduced cortical actin density and phospholipid PIP2. These data resolve the temporal order of events during synapse maturation in 4D and reveal a critical role for actin depletion in regulating secretion.
The cellular mechanisms governing non-muscle myosin II (NM2) filament assembly are largely unknown. Using EGFP-NM2A knock-in fibroblasts and multiple super-resolution imaging modalities, we characterized and quantified the sequential amplification of NM2 filaments within lamellae, wherein filaments emanating from single nucleation events continuously partition, forming filament clusters that populate large-scale actomyosin structures deeper in the cell. Individual partitioning events coincide spatially and temporally with the movements of diverging actin fibres, suppression of which inhibits partitioning. These and other data indicate that NM2A filaments are partitioned by the dynamic movements of actin fibres to which they are bound. Finally, we showed that partition frequency and filament growth rate in the lamella depend on MLCK, and that MLCK is competing with centrally active ROCK for a limiting pool of monomer with which to drive lamellar filament assembly. Together, our results provide new insights into the mechanism and spatio-temporal regulation of NM2 filament assembly in cells.
Podosomes are actin-enriched adhesion structures important for multiple cellular processes, including migration, bone remodeling, and phagocytosis. Here, we characterized the structure and organization of phagocytic podosomes using interferometric photoactivated localization microscopy (iPALM), a super-resolution microscopy technique capable of 15-20 nm resolution, together with structured illumination microscopy (SIM) and localization-based superresolution microscopy. Phagocytic podosomes were observed during frustrated phagocytosis, a model in which cells attempt to engulf micro-patterned IgG antibodies. For circular patterns, this resulted in regular arrays of podosomes with well-defined geometry. Using persistent homology, we developed a pipeline for semi-automatic identification and measurement of podosome features. These studies revealed an "hourglass" shape of the podosome actin core, a protruding "knob" at the bottom of the core, and two actin networks extending from the core. Additionally, the distributions of paxillin, talin, myosin II, α-actinin, cortactin, and microtubules relative to actin were characterized.
Leukocytes and other amoeboid cells change shape as they move, forming highly dynamic, actin-filled pseudopods. Although we understand much about the architecture and dynamics of thin lamellipodia made by slow-moving cells on flat surfaces, conventional light microscopy lacks the spatial and temporal resolution required to track complex pseudopods of cells moving in three dimensions. We therefore employed lattice light sheet microscopy to perform three-dimensional, time-lapse imaging of neutrophil-like HL-60 cells crawling through collagen matrices. To analyze three-dimensional pseudopods we: (i) developed fluorescent probe combinations that distinguish cortical actin from dynamic, pseudopod-forming actin networks, and (ii) adapted molecular visualization tools from structural biology to render and analyze complex cell surfaces. Surprisingly, three-dimensional pseudopods turn out to be composed of thin (<0.75 µm), flat sheets that sometimes interleave to form rosettes. Their laminar nature is not templated by an external surface, but likely reflects a linear arrangement of regulatory molecules. Although we find that Arp2/3-dependent pseudopods are dispensable for three-dimensional locomotion, their elimination dramatically decreases the frequency of cell turning, and pseudopod dynamics increase when cells change direction, highlighting the important role pseudopods play in pathfinding.
We present a Bayesian framework for action recognition through ballistic dynamics. Psycho-kinesiological studies indicate that ballistic movements form the natural units for human movement planning. The framework leads to an efficient and robust algorithm for temporally segmenting videos into atomic movements. Individual movements are annotated with person-centric morphological labels called ballistic verbs. This is tested on a dataset of interactive movements, achieving high recognition rates. The approach is also applied on a gesture recognition task, improving a previously reported recognition rate from 84% to 92%. Consideration of ballistic dynamics enhances the performance of the popular Motion History Image feature. We also illustrate the approach’s general utility on real-world videos. Experiments indicate that the method is robust to view, style and appearance variations.
The physiology of N-methyl-d-aspartate (NMDA) receptors is fundamental to brain development and function. NMDA receptors are ionotropic glutamate receptors that function as heterotetramers composed mainly of GluN1 and GluN2 subunits. Activation of NMDA receptors requires binding of neurotransmitter agonists to a ligand-binding domain (LBD) and structural rearrangement of an amino-terminal domain (ATD). Recent crystal structures of GluN1-GluN2B NMDA receptors bound to agonists and an allosteric inhibitor, ifenprodil, represent the allosterically inhibited state. However, how the ATD and LBD move to activate the NMDA receptor ion channel remains unclear. Here we applied X-ray crystallography, single-particle electron cryomicroscopy and electrophysiology to rat NMDA receptors to show that, in the absence of ifenprodil, the bi-lobed structure of GluN2 ATD adopts an open conformation accompanied by rearrangement of the GluN1-GluN2 ATD heterodimeric interface, altering subunit orientation in the ATD and LBD and forming an active receptor conformation that gates the ion channel.
Animals strategically scan the environment to form an accurate perception of their surroundings. Here we investigated the neuronal representations that mediate this behavior. Ca imaging and selective optogenetic manipulation during an active sensing task reveals that layer 5 pyramidal neurons in the vibrissae cortex produce a diverse and distributed representation that is required for mice to adapt their whisking motor strategy to changing sensory cues. The optogenetic perturbation degraded single-neuron selectivity and network population encoding through a selective inhibition of active dendritic integration. Together the data indicate that active dendritic integration in pyramidal neurons produces a nonlinearly mixed network representation of joint sensorimotor parameters that is used to transform sensory information into motor commands during adaptive behavior. The prevalence of the layer 5 cortical circuit motif suggests that this is a general circuit computation.
UNLABELLED: Neurons respond to specific features of sensory stimuli. In the visual system, for example, some neurons respond to motion of small but not large objects, whereas other neurons prefer motion of the entire visual field. Separate neurons respond equally to local and global motion but selectively to additional features of visual stimuli. How and where does response selectivity emerge? Here, we show that wide-field (WF) cells in retino-recipient layers of the mouse superior colliculus (SC) respond selectively to small moving objects. Moreover, we identify two mechanisms that contribute to this selectivity. First, we show that input restricted to a small portion of the broad dendritic arbor of WF cells is sufficient to trigger dendritic spikes that reliably propagate to the soma/axon. In vivo whole-cell recordings reveal that nearly every action potential evoked by visual stimuli has characteristics of spikes initiated in dendrites. Second, inhibitory input from a different class of SC neuron, horizontal cells, constrains the range of stimuli to which WF cells respond. Horizontal cells respond preferentially to the sudden appearance or rapid movement of large stimuli. Optogenetic reduction of their activity reduces movement selectivity and broadens size tuning in WF cells by increasing the relative strength of responses to stimuli that appear suddenly or cover a large region of space. Therefore, strongly propagating dendritic spikes enable small stimuli to drive spike output in WF cells and local inhibition helps restrict responses to stimuli that are both small and moving. SIGNIFICANCE STATEMENT: How do neurons respond selectively to some sensory stimuli but not others? In the visual system, a particularly relevant stimulus feature is object motion, which often reveals other animals. Here, we show how specific cells in the superior colliculus, one synapse downstream of the retina, respond selectively to object motion. These wide-field (WF) cells respond strongly to small objects that move slowly anywhere through a large region of space, but not to stationary objects or full-field motion. Action potential initiation in dendrites enables small stimuli to trigger visual responses and inhibitory input from cells that prefer large, suddenly appearing, or quickly moving stimuli restricts responses of WF cells to objects that are small and moving.
The CA3 and CA1 pyramidal neurons are the major principal cell types of the hippocampus proper. The strongly recurrent collateral system of CA3 cells and the largely parallel-organized CA1 neurons suggest that these regions perform distinct computations. However, a comprehensive comparison between CA1 and CA3 pyramidal cells in terms of firing properties, network dynamics, and behavioral correlations is sparse in the intact animal. We performed large-scale recordings in the dorsal hippocampus of rats to quantify the similarities and differences between CA1 (n > 3,600) and CA3 (n > 2,200) pyramidal cells during sleep and exploration in multiple environments. CA1 and CA3 neurons differed significantly in firing rates, spike burst propensity, spike entrainment by the theta rhythm, and other aspects of spiking dynamics in a brain state-dependent manner. A smaller proportion of CA3 than CA1 cells displayed prominent place fields, but place fields of CA3 neurons were more compact, more stable, and carried more spatial information per spike than those of CA1 pyramidal cells. Several other features of the two cell types were specific to the testing environment. CA3 neurons showed less pronounced phase precession and a weaker position versus spike-phase relationship than CA1 cells. Our findings suggest that these distinct activity dynamics of CA1 and CA3 pyramidal cells support their distinct computational roles.
Cortical-feedback projections to primary sensory areas terminate most heavily in layer 1 (L1) of the neocortex, where they make synapses with tuft dendrites of pyramidal neurons. L1 input is thought to provide ‘contextual’ information, but the signals transmitted by L1 feedback remain uncharacterized. In the rodent somatosensory system, the spatially diffuse feedback projection from vibrissal motor cortex (vM1) to vibrissal somatosensory cortex (vS1, also known as the barrel cortex) may allow whisker touch to be interpreted in the context of whisker position to compute object location. When mice palpate objects with their whiskers to localize object features, whisker touch excites vS1 and later vM1 in a somatotopic manner. Here we use axonal calcium imaging to track activity in vM1–>vS1 afferents in L1 of the barrel cortex while mice performed whisker-dependent object localization. Spatially intermingled individual axons represent whisker movements, touch and other behavioural features. In a subpopulation of axons, activity depends on object location and persists for seconds after touch. Neurons in the barrel cortex thus have information to integrate movements and touches of multiple whiskers over time, key components of object identification and navigation by active touch.