Filter
Associated Lab
- Aguilera Castrejon Lab (14) Apply Aguilera Castrejon Lab filter
- Ahrens Lab (52) Apply Ahrens Lab filter
- Aso Lab (39) Apply Aso Lab filter
- Baker Lab (38) Apply Baker Lab filter
- Betzig Lab (110) Apply Betzig Lab filter
- Beyene Lab (9) Apply Beyene Lab filter
- Bock Lab (17) Apply Bock Lab filter
- Branson Lab (48) Apply Branson Lab filter
- Card Lab (38) Apply Card Lab filter
- Cardona Lab (63) Apply Cardona Lab filter
- Chklovskii Lab (13) Apply Chklovskii Lab filter
- Clapham Lab (11) Apply Clapham Lab filter
- Cui Lab (19) Apply Cui Lab filter
- Darshan Lab (12) Apply Darshan Lab filter
- Dennis Lab (1) Apply Dennis Lab filter
- Dickson Lab (46) Apply Dickson Lab filter
- Druckmann Lab (25) Apply Druckmann Lab filter
- Dudman Lab (46) Apply Dudman Lab filter
- Eddy/Rivas Lab (30) Apply Eddy/Rivas Lab filter
- Egnor Lab (11) Apply Egnor Lab filter
- Espinosa Medina Lab (16) Apply Espinosa Medina Lab filter
- Feliciano Lab (6) Apply Feliciano Lab filter
- Fetter Lab (41) Apply Fetter Lab filter
- Fitzgerald Lab (27) Apply Fitzgerald Lab filter
- Freeman Lab (15) Apply Freeman Lab filter
- Funke Lab (33) Apply Funke Lab filter
- Gonen Lab (91) Apply Gonen Lab filter
- Grigorieff Lab (62) Apply Grigorieff Lab filter
- Harris Lab (57) Apply Harris Lab filter
- Heberlein Lab (94) Apply Heberlein Lab filter
- Hermundstad Lab (21) Apply Hermundstad Lab filter
- Hess Lab (68) Apply Hess Lab filter
- Jayaraman Lab (43) Apply Jayaraman Lab filter
- Ji Lab (32) Apply Ji Lab filter
- Johnson Lab (6) Apply Johnson Lab filter
- Kainmueller Lab (19) Apply Kainmueller Lab filter
- Karpova Lab (14) Apply Karpova Lab filter
- Keleman Lab (13) Apply Keleman Lab filter
- Keller Lab (75) Apply Keller Lab filter
- Koay Lab (16) Apply Koay Lab filter
- Lavis Lab (131) Apply Lavis Lab filter
- Lee (Albert) Lab (34) Apply Lee (Albert) Lab filter
- Leonardo Lab (23) Apply Leonardo Lab filter
- Li Lab (25) Apply Li Lab filter
- Lippincott-Schwartz Lab (155) Apply Lippincott-Schwartz Lab filter
- Liu (Yin) Lab (5) Apply Liu (Yin) Lab filter
- Liu (Zhe) Lab (56) Apply Liu (Zhe) Lab filter
- Looger Lab (137) Apply Looger Lab filter
- Magee Lab (49) Apply Magee Lab filter
- Menon Lab (18) Apply Menon Lab filter
- Murphy Lab (13) Apply Murphy Lab filter
- O'Shea Lab (4) Apply O'Shea Lab filter
- Otopalik Lab (1) Apply Otopalik Lab filter
- Pachitariu Lab (38) Apply Pachitariu Lab filter
- Pastalkova Lab (18) Apply Pastalkova Lab filter
- Pavlopoulos Lab (19) Apply Pavlopoulos Lab filter
- Pedram Lab (12) Apply Pedram Lab filter
- Podgorski Lab (16) Apply Podgorski Lab filter
- Reiser Lab (48) Apply Reiser Lab filter
- Riddiford Lab (44) Apply Riddiford Lab filter
- Romani Lab (40) Apply Romani Lab filter
- Rubin Lab (138) Apply Rubin Lab filter
- Saalfeld Lab (58) Apply Saalfeld Lab filter
- Satou Lab (16) Apply Satou Lab filter
- Scheffer Lab (36) Apply Scheffer Lab filter
- Schreiter Lab (61) Apply Schreiter Lab filter
- Sgro Lab (20) Apply Sgro Lab filter
- Shroff Lab (18) Apply Shroff Lab filter
- Simpson Lab (23) Apply Simpson Lab filter
- Singer Lab (80) Apply Singer Lab filter
- Spruston Lab (91) Apply Spruston Lab filter
- Stern Lab (150) Apply Stern Lab filter
- Sternson Lab (54) Apply Sternson Lab filter
- Stringer Lab (24) Apply Stringer Lab filter
- Svoboda Lab (135) Apply Svoboda Lab filter
- Tebo Lab (30) Apply Tebo Lab filter
- Tervo Lab (9) Apply Tervo Lab filter
- Tillberg Lab (15) Apply Tillberg Lab filter
- Tjian Lab (64) Apply Tjian Lab filter
- Truman Lab (88) Apply Truman Lab filter
- Turaga Lab (46) Apply Turaga Lab filter
- Turner Lab (35) Apply Turner Lab filter
- Vale Lab (6) Apply Vale Lab filter
- Voigts Lab (1) Apply Voigts Lab filter
- Wang (Meng) Lab (6) Apply Wang (Meng) Lab filter
- Wang (Shaohe) Lab (20) Apply Wang (Shaohe) Lab filter
- Wu Lab (9) Apply Wu Lab filter
- Zlatic Lab (28) Apply Zlatic Lab filter
- Zuker Lab (25) Apply Zuker Lab filter
Associated Project Team
- CellMap (1) 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 (48) Apply FlyEM filter
- FlyLight (45) Apply FlyLight filter
- GENIE (38) 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) (21) Apply Tool Translation Team (T3) filter
- Transcription Imaging (49) Apply Transcription Imaging filter
Publication Date
- 2024 (64) Apply 2024 filter
- 2023 (179) Apply 2023 filter
- 2022 (191) Apply 2022 filter
- 2021 (192) Apply 2021 filter
- 2020 (196) Apply 2020 filter
- 2019 (199) Apply 2019 filter
- 2018 (232) Apply 2018 filter
- 2017 (214) Apply 2017 filter
- 2016 (209) Apply 2016 filter
- 2015 (250) Apply 2015 filter
- 2014 (236) Apply 2014 filter
- 2013 (194) Apply 2013 filter
- 2012 (189) Apply 2012 filter
- 2011 (190) Apply 2011 filter
- 2010 (161) Apply 2010 filter
- 2009 (158) Apply 2009 filter
- 2008 (140) Apply 2008 filter
- 2007 (106) Apply 2007 filter
- 2006 (92) Apply 2006 filter
- 2005 (67) Apply 2005 filter
- 2004 (57) Apply 2004 filter
- 2003 (58) Apply 2003 filter
- 2002 (39) Apply 2002 filter
- 2001 (28) Apply 2001 filter
- 2000 (29) Apply 2000 filter
- 1999 (14) Apply 1999 filter
- 1998 (18) Apply 1998 filter
- 1997 (16) Apply 1997 filter
- 1996 (10) Apply 1996 filter
- 1995 (18) Apply 1995 filter
- 1994 (12) Apply 1994 filter
- 1993 (10) Apply 1993 filter
- 1992 (6) Apply 1992 filter
- 1991 (11) Apply 1991 filter
- 1990 (11) Apply 1990 filter
- 1989 (6) Apply 1989 filter
- 1988 (1) Apply 1988 filter
- 1987 (7) Apply 1987 filter
- 1986 (4) Apply 1986 filter
- 1985 (5) Apply 1985 filter
- 1984 (2) Apply 1984 filter
- 1983 (2) Apply 1983 filter
- 1982 (3) Apply 1982 filter
- 1981 (3) Apply 1981 filter
- 1980 (1) Apply 1980 filter
- 1979 (1) Apply 1979 filter
- 1976 (2) Apply 1976 filter
- 1973 (1) Apply 1973 filter
- 1970 (1) Apply 1970 filter
- 1967 (1) Apply 1967 filter
Type of Publication
3836 Publications
Showing 1321-1330 of 3836 resultsProgress in modern neuroscience critically depends on our ability to observe the activity of large neuronal populations with cellular spatial and high temporal resolution. However, two bottlenecks constrain efforts towards fast imaging of large populations. First, the resulting large video data is challenging to analyze. Second, there is an explicit tradeoff between imaging speed, signal-to-noise, and field of view: with current recording technology we cannot image very large neuronal populations with simultaneously high spatial and temporal resolution. Here we describe multi-scale approaches for alleviating both of these bottlenecks. First, we show that spatial and temporal decimation techniques based on simple local averaging provide order-of-magnitude speedups in spatiotemporally demixing calcium video data into estimates of single-cell neural activity. Second, once the shapes of individual neurons have been identified at fine scale (e.g., after an initial phase of conventional imaging with standard temporal and spatial resolution), we find that the spatial/temporal resolution tradeoff shifts dramatically: after demixing we can accurately recover denoised fluorescence traces and deconvolved neural activity of each individual neuron from coarse scale data that has been spatially decimated by an order of magnitude. This offers a cheap method for compressing this large video data, and also implies that it is possible to either speed up imaging significantly, or to "zoom out" by a corresponding factor to image order-of-magnitude larger neuronal populations with minimal loss in accuracy or temporal resolution.
Adjusting the objective correction collar is a widely used approach to correct spherical aberrations (SA) in optical microscopy. In this work, we characterized and compared its performance with adaptive optics in the context of in vivo brain imaging with two-photon fluorescence microscopy. We found that the presence of sample tilt had a deleterious effect on the performance of SA-only correction. At large tilt angles, adjusting the correction collar even worsened image quality. In contrast, adaptive optical correction always recovered optimal imaging performance regardless of sample tilt. The extent of improvement with adaptive optics was dependent on object size, with smaller objects having larger relative gains in signal intensity and image sharpness. These observations translate into a superior performance of adaptive optics for structural and functional brain imaging applications in vivo, as we confirmed experimentally.
The present disclosure provides, inter alia, genetically encoded recombinant peptide biosensors comprising analyte-binding framework portions and signaling portions, wherein the signaling portions are present within the framework portions at sites or amino acid positions that undergo a conformational change upon interaction of the framework portion with an analyte.
A system for a laser-scanning microscope includes an optical element configured to transmit light in a first direction onto a first beam path and to reflect light in a second direction to a second beam path that is different from the first beam path; a reflector on the first beam path; and a lens including a variable focal length, the lens positioned on the first beam path. The lens and reflector are positioned relative to each other to cause light transmitted by the optical element to pass through the lens a plurality of times and in a different direction each time. In some implementations, the system also can include a feedback system that receives a signal that represents an amount of focusing of the lens, and changes the focal length of the lens based on the received signal.
Transcriptional enhancers are regions of DNA that drive precise patterns of gene expression. While many studies have elucidated how individual enhancers can evolve, most of this work has focused on what are called "minimal" enhancers, the smallest DNA regions that drive expression that approximates an aspect of native gene expression. Here we explore how the Drosophila erecta even-skipped (eve) locus has evolved by testing its activity in the divergent D. melanogaster genome. We found, as has been reported previously, that the D. erecta eve stripe 2 enhancer (eveS2) fails to drive appreciable expression in D. melanogaster (1). However, we found that a large transgene carrying the entire D. erecta eve locus drives normal eve expression, including in stripe 2. We performed a functional dissection of the region upstream of the D. erecta eveS2 region and found multiple Zelda motifs that are required for normal expression. Our results illustrate how sequences outside of minimal enhancer regions can evolve functionally through mechanisms other than changes in transcription factor binding sites that drive patterning.
The extracellular matrix (ECM) regulates cell migration and sculpts organ shape. AdamTS proteins are extracellular metalloproteases known to modify ECM proteins and promote cell migration, but demonstrated roles for AdamTS proteins in regulating CNS structure and ensuring cell lineages remain fixed in place have not been uncovered. Using forward genetic approaches in Drosophila, we find that reduction of AdamTS-A function induces both the mass exodus of neural lineages out of the CNS and drastic perturbations to CNS structure. Expressed and active in surface glia, AdamTS-A acts in parallel to perlecan and in opposition to viking/collagen IV and βPS-integrin to keep CNS lineages rooted in place and to preserve the structural integrity of the CNS. viking/collagen IV and βPS-integrin are known to promote tissue stiffness and oppose the function of perlecan, which reduces tissue stiffness. Our work supports a model in which AdamTS-A anchors cells in place and preserves CNS architecture by reducing tissue stiffness.
The serotonergic system in the vertebrate brain is implicated in various behaviors and diseases. Its involvement in motor control has been studied for over half a century, but efforts to build a unified model of its functions have been hampered due to the complexity of serotonergic neuromodulation. This review summarizes the anatomical structure of the serotonergic system, its afferent and efferent connections to other brain regions, and recent insights into the sensorimotor computations in the serotonergic system, and considers future research directions into the roles of serotonergic system in motor control.
Animals execute one particular behavior among many others in a context-dependent manner, yet the mechanisms underlying such behavioral choice remain poorly understood. Here we studied how two fundamental behaviors, sex and sleep, interact at genetic and neuronal levels in Drosophila. We show that an increased need for sleep inhibits male sexual behavior by decreasing the activity of the male-specific P1 neurons that coexpress the sex determination genes fru (M) and dsx, but does not affect female sexual behavior. Further, we delineate a sex-specific neuronal circuit wherein the P1 neurons encoding increased courtship drive suppressed male sleep by forming mutually excitatory connections with the fru (M) -positive sleep-controlling DN1 neurons. In addition, we find that FRU(M) regulates male courtship and sleep through distinct neural substrates. These studies reveal the genetic and neuronal basis underlying the sex-specific interaction between sleep and sexual behaviors in Drosophila, and provide insights into how competing behaviors are co-regulated.Genes and circuits involved in sleep and sexual arousal have been extensively studied in Drosophila. Here the authors identify the sex determination genes fruitless and doublesex, and a sex-specific P1-DN1 neuronal feedback that governs the interaction between these competing behaviors.
50 years ago, Vincent Allfrey and colleagues discovered that lymphocyte activation triggers massive acetylation of chromatin. However, the molecular mechanisms driving epigenetic accessibility are still unknown. We here show that stimulated lymphocytes decondense chromatin by three differentially regulated steps. First, chromatin is repositioned away from the nuclear periphery in response to global acetylation. Second, histone nanodomain clusters decompact into mononucleosome fibers through a mechanism that requires Myc and continual energy input. Single-molecule imaging shows that this step lowers transcription factor residence time and non-specific collisions during sampling for DNA targets. Third, chromatin interactions shift from long range to predominantly short range, and CTCF-mediated loops and contact domains double in numbers. This architectural change facilitates cognate promoter-enhancer contacts and also requires Myc and continual ATP production. Our results thus define the nature and transcriptional impact of chromatin decondensation and reveal an unexpected role for Myc in the establishment of nuclear topology in mammalian cells.
Like all other secretory proteins, the HIV-1 envelope glycoprotein gp160, is targeted to the endoplasmic reticulum (ER) by its signal peptide during synthesis. Proper gp160 folding in the ER requires core glycosylation, disulfide-bond formation and proline isomerization. Signal-peptide cleavage occurs only late after gp160 chain termination and is dependent on folding of the soluble subunit gp120 to a near-native conformation. We here detail the mechanism by which co-translational signal-peptide cleavage is prevented. Conserved residues from the signal peptide and residues downstream of the canonical cleavage site form an extended alpha-helix in the ER membrane that covers the cleavage site, thus preventing cleavage. A point mutation in the signal peptide breaks the alpha helix allowing co-translational cleavage. We demonstrate that postponed cleavage of gp160 enhances functional folding of the molecule. The change to early cleavage results in decreased viral fitness compared to wild-type HIV.