Filter
Associated Lab
- Aguilera Castrejon Lab (15) Apply Aguilera Castrejon Lab filter
- Ahrens Lab (57) Apply Ahrens Lab filter
- Aso Lab (39) Apply Aso Lab filter
- Baker Lab (38) Apply Baker Lab filter
- Betzig Lab (111) Apply Betzig Lab filter
- Beyene Lab (10) Apply Beyene Lab filter
- Bock Lab (17) Apply Bock Lab filter
- Branson Lab (48) Apply Branson Lab filter
- Card Lab (40) Apply Card Lab filter
- Cardona Lab (63) Apply Cardona Lab filter
- Chklovskii Lab (13) Apply Chklovskii Lab filter
- Clapham Lab (13) 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 (28) Apply Fitzgerald Lab filter
- Freeman Lab (15) Apply Freeman Lab filter
- Funke Lab (35) Apply Funke Lab filter
- Gonen Lab (91) Apply Gonen Lab filter
- Grigorieff Lab (62) Apply Grigorieff Lab filter
- Harris Lab (58) Apply Harris Lab filter
- Heberlein Lab (94) Apply Heberlein Lab filter
- Hermundstad Lab (22) Apply Hermundstad Lab filter
- Hess Lab (72) Apply Hess Lab filter
- Ilanges Lab (1) Apply Ilanges Lab filter
- Jayaraman Lab (44) Apply Jayaraman Lab filter
- Ji Lab (33) 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 (17) Apply Koay Lab filter
- Lavis Lab (138) Apply Lavis Lab filter
- Lee (Albert) Lab (34) Apply Lee (Albert) Lab filter
- Leonardo Lab (23) Apply Leonardo Lab filter
- Li Lab (27) Apply Li Lab filter
- Lippincott-Schwartz Lab (161) Apply Lippincott-Schwartz Lab filter
- Liu (Yin) Lab (5) Apply Liu (Yin) Lab filter
- Liu (Zhe) Lab (61) 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 (6) Apply O'Shea Lab filter
- Otopalik Lab (13) Apply Otopalik Lab filter
- Pachitariu Lab (42) Apply Pachitariu Lab filter
- Pastalkova Lab (18) Apply Pastalkova Lab filter
- Pavlopoulos Lab (19) Apply Pavlopoulos Lab filter
- Pedram Lab (14) Apply Pedram Lab filter
- Podgorski Lab (16) Apply Podgorski Lab filter
- Reiser Lab (49) Apply Reiser Lab filter
- Riddiford Lab (44) Apply Riddiford Lab filter
- Romani Lab (41) Apply Romani Lab filter
- Rubin Lab (139) Apply Rubin Lab filter
- Saalfeld Lab (61) Apply Saalfeld Lab filter
- Satou Lab (16) Apply Satou Lab filter
- Scheffer Lab (36) Apply Scheffer Lab filter
- Schreiter Lab (62) Apply Schreiter Lab filter
- Sgro Lab (20) Apply Sgro Lab filter
- Shroff Lab (24) 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 (152) Apply Stern Lab filter
- Sternson Lab (54) Apply Sternson Lab filter
- Stringer Lab (29) Apply Stringer Lab filter
- Svoboda Lab (135) Apply Svoboda Lab filter
- Tebo Lab (31) Apply Tebo Lab filter
- Tervo Lab (9) Apply Tervo Lab filter
- Tillberg Lab (17) 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 (2) Apply Voigts Lab filter
- Wang (Meng) Lab (10) Apply Wang (Meng) Lab filter
- Wang (Shaohe) Lab (24) 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 (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 (49) Apply Transcription Imaging filter
Publication Date
- 2024 (170) Apply 2024 filter
- 2023 (171) Apply 2023 filter
- 2022 (192) Apply 2022 filter
- 2021 (193) Apply 2021 filter
- 2020 (196) Apply 2020 filter
- 2019 (202) Apply 2019 filter
- 2018 (232) Apply 2018 filter
- 2017 (217) Apply 2017 filter
- 2016 (209) Apply 2016 filter
- 2015 (252) Apply 2015 filter
- 2014 (236) Apply 2014 filter
- 2013 (194) Apply 2013 filter
- 2012 (190) 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
3945 Publications
Showing 1171-1180 of 3945 resultsLearning through trial-and-error interactions allows animals to adapt innate behavioural ‘rules of thumb’ to the local environment, improving their prospects for survival and reproduction. Naive Drosophila melanogaster males, for example, court both virgin and mated females, but learn through experience to selectively suppress futile courtship towards females that have already mated. Here we show that courtship learning reflects an enhanced response to the male pheromone cis-vaccenyl acetate (cVA), which is deposited on females during mating and thus distinguishes mated females from virgins. Dissociation experiments suggest a simple learning rule in which unsuccessful courtship enhances sensitivity to cVA. The learning experience can be mimicked by artificial activation of dopaminergic neurons, and we identify a specific class of dopaminergic neuron that is critical for courtship learning. These neurons provide input to the mushroom body (MB) γ lobe, and the DopR1 dopamine receptor is required in MBγ neurons for both natural and artificial courtship learning. Our work thus reveals critical behavioural, cellular and molecular components of the learning rule by which Drosophila adjusts its innate mating strategy according to experience.
Associative learning is thought to involve parallel and distributed mechanisms of memory formation and storage. In Drosophila, the mushroom body (MB) is the major site of associative odor memory formation. Previously we described the anatomy of the adult MB and defined 20 types of dopaminergic neurons (DANs) that each innervate distinct MB compartments (Aso et al., 2014a; Aso et al., 2014b). Here we compare the properties of memories formed by optogenetic activation of individual DAN cell types. We found extensive differences in training requirements for memory formation, decay dynamics, storage capacity and flexibility to learn new associations. Even a single DAN cell type can either write or reduce an aversive memory, or write an appetitive memory, depending on when it is activated relative to odor delivery. Our results show that different learning rules are executed in seemingly parallel memory systems, providing multiple distinct circuit-based strategies to predict future events from past experiences.
Histochemical examination of the dorsorostral quadrant of the rat snout revealed superficial and deep muscles that are involved in whisking, sniffing, and airflow control. The part of M. nasolabialis profundus that acts as an intrinsic (follicular) muscle to facilitate protraction and translation of the vibrissae is described. An intraturbinate and selected rostral-most nasal muscles that can influence major routs of inspiratory airflow and rhinarial touch through their control of nostril configuration, atrioturbinate and rhinarium position, were revealed.
The eye imaginal disc displays dorsal-ventral (D-V) and anterior-posterior polarity prior to the onset of differentiation, which initiates at the intersection of the D-V midline with the posterior margin. As the wave of differentiation progresses anteriorly, additional asymmetry develops as ommatidial clusters rotate coordinately in opposite directions in the dorsal and ventral halves of the disc; this forms a line of mirror-image symmetry, the equator, which coincides with the D-V midline of the disc. How D-V pattern is established and how it relates to ommatidial rotation are unknown. Here we address this question by assaying the expression of various asymmetric markers under conditions that lead to ectopic differentiation, such as removal of patched or wingless function. We find that D-V patterning develops gradually and that wingless plays an important role in setting up this pattern. We show that wingless is necessary and sufficient to induce dorsal expression of the gene mirror prior to the start of differentiation and also to restrict the expression of the WR122 marker to differentiating photoreceptors near the equator. In addition, we find that manipulations in wingless expression shift the D-V axis of the disc as evidenced by changes in the expression domains of asymmetric markers, the position of the site of initiation and the equator, and the pattern of epithelial growth. Thus, Wg appears to coordinately regulate multiple events related to D-V patterning in the developing retina.
Somatic sexual dimorphisms outside of the nervous system in Drosophila melanogaster are largely controlled by the male- and female-specific Doublesex transcription factors (DSX(M) and DSX(F), respectively). The DSX proteins must act at the right times and places in development to regulate the diverse array of genes that sculpt male and female characteristics across a variety of tissues. To explore how cellular and developmental contexts integrate with doublesex (dsx) gene function, we focused on the sexually dimorphic number of gustatory sense organs (GSOs) in the foreleg. We show that DSX(M) and DSX(F) promote and repress GSO formation, respectively, and that their relative contribution to this dimorphism varies along the proximodistal axis of the foreleg. Our results suggest that the DSX proteins impact specification of the gustatory sensory organ precursors (SOPs). DSX(F) then acts later in the foreleg to regulate gustatory receptor neuron axon guidance. These results suggest that the foreleg provides a unique opportunity for examining the context-dependent functions of DSX.
It is unclear how regulatory genes establish neural circuits that compose sex-specific behaviors. The Drosophila melanogaster male courtship song provides a powerful model to study this problem. Courting males vibrate a wing to sing bouts of pulses and hums, called pulse and sine song, respectively. We report the discovery of male-specific thoracic interneurons—the TN1A neurons—that are required specifically for sine song. The TN1A neurons can drive the activity of a sex-non-specific wing motoneuron, hg1, which is also required for sine song. The male-specific connection between the TN1A neurons and the hg1 motoneuron is regulated by the sexual differentiation gene doublesex. We find that doublesex is required in the TN1A neurons during development to increase the density of the TN1A arbors that interact with dendrites of the hg1motoneuron. Our findings demonstrate how a sexual differentiation gene can build a sex-specific circuit motif by modulating neuronal arborization. •Doublesex-expressing TN1 neurons are necessary and sufficient for the male sine song•A subclass of TN1 neurons, TN1A, contributes to the sine song•TN1A neurons are functionally coupled to a sine song motoneuron, hg1•Doublesex regulates the connectivity between the TN1A and hg1 neurons It is unclear how developmental regulatory genes specify sex-specific behaviors. Shirangi et al. demonstrate that the Drosophila sexual differentiation gene doublesex encodes a sex-specific behavior—male song—by promoting the connectivity between the male-specific TN1A neurons and the sex-non-specific hg1 neurons, which are required for production of the song.
Pharmacological and genetic studies have implicated the mu opioid receptor (MOR) in the regulation of ethanol intake in animal models and humans. Non-specific antagonists of opioid receptors have been shown to affect ethanol consumption when infused directly into the ventral tegmental area (VTA) of rats. However, administration of MOR-selective antagonists into the VTA has yielded mixed results. We used RNA interference (RNAi) to specifically decrease levels of MOR messenger RNA in the VTA of mice and examined the effect on ethanol consumption in a two-bottle choice paradigm. Mice were injected in the VTA with lentivirus expressing either a small hairpin RNA (shRNA) targeting MOR or a control shRNA. One week after virus injection, mice were examined for ethanol consumption in a two-bottle choice experiment with increasing concentrations of ethanol over the course of 1 month. Expression of an shRNA targeting MOR in the VTA led to a significant reduction in ethanol consumption. These results strengthen the hypothesis that MOR in the VTA is one of the key brain substrates mediating alcohol consumption. The RNAi combined with lentiviral delivery can be used successfully in brain to effect a sustained reduction in expression of specific genes for behavioral analysis.
The mushroom body (MB) is the center for associative learning in insects. In Drosophila, intersectional split-GAL4 drivers and electron microscopy (EM) connectomes have laid the foundation for precise interrogation of the MB neural circuits. However, many cell types upstream and downstream of the MB remained to be investigated due to lack of driver lines. Here we describe a new collection of over 800 split-GAL4 and split-LexA drivers that cover approximately 300 cell types, including sugar sensory neurons, putative nociceptive ascending neurons, olfactory and thermo-/hygro-sensory projection neurons, interneurons connected with the MB-extrinsic neurons, and various other cell types. We characterized activation phenotypes for a subset of these lines and identified the sugar sensory neuron line most suitable for reward substitution. Leveraging the thousands of confocal microscopy images associated with the collection, we analyzed neuronal morphological stereotypy and discovered that one set of mushroom body output neurons, MBON08/MBON09, exhibits striking individuality and asymmetry across animals. In conjunction with the EM connectome maps, the driver lines reported here offer a powerful resource for functional dissection of neural circuits for associative learning in adult Drosophila.
We describe a method for molecular confinement and single-fluorophore sensitive measurement in aqueous nanodroplets in oil. The sequestration of individual molecules in droplets has become a useful tool in genomics and molecular evolution. Similarly, the use of single fluorophores, or pairs of fluorophores, to study biomolecular interactions and structural dynamics is now common. Most often these single-fluorophore sensitive measurements are performed on molecules that are surface attached. Confinement via surface attachment permits molecules to be located and studied for a prolonged period of time. For molecules that denature on surfaces, for interactions that are transient or out-of-equilibrium, or to observe the dynamic equilibrium of freely diffusing reagents, surface attachment may not be an option. In these cases, droplet confinement presents an alternative method for molecular confinement. Here, we describe this method as used in single-fluorophore sensitive measurement and discuss its advantages, limitations, and future prospects.
This paper describes a platform for cooling microfluidic chips so as to freeze aqueous droplets flowing in oil. Using a whole-chip cooling chamber, we can control the ambient temperature surrounding a microfluidic chip and induce cooling and freezing inside the channels. When combined with a droplet generation and droplet docking chip, this platform allows for the facile freezing of droplets immobilized in resistance-based docks. Depending on the design and shape of the docks, the frozen droplets can either be trapped stably in the docks or be released because deformed non-frozen aqueous droplets turn spherical when frozen, and thus can become dislodged from the docks. Additionally, using this chamber and chip combination we are able to exchange immiscible phases and surfactants surrounding the frozen droplets. The materials and methods are inexpensive and easily accessible to microfluidics researchers, making this a simple addition to an existing microfluidic platform.