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2578 Janelia Publications
Showing 2351-2360 of 2578 resultsAversive olfactory memory is formed in the mushroom bodies in Drosophila melanogaster. Memory retrieval requires mushroom body output, but the manner in which a memory trace in the mushroom body drives conditioned avoidance of a learned odor remains unknown. To identify neurons that are involved in olfactory memory retrieval, we performed an anatomical and functional screen of defined sets of mushroom body output neurons. We found that MB-V2 neurons were essential for retrieval of both short- and long-lasting memory, but not for memory formation or memory consolidation. MB-V2 neurons are cholinergic efferent neurons that project from the mushroom body vertical lobes to the middle superiormedial protocerebrum and the lateral horn. Notably, the odor response of MB-V2 neurons was modified after conditioning. As the lateral horn has been implicated in innate responses to repellent odorants, we propose that MB-V2 neurons recruit the olfactory pathway involved in innate odor avoidance during memory retrieval.
The ability of insects to learn and navigate to specific locations in the environment has fascinated naturalists for decades. The impressive navigational abilities of ants, bees, wasps and other insects demonstrate that insects are capable of visual place learning, but little is known about the underlying neural circuits that mediate these behaviours. Drosophila melanogaster (common fruit fly) is a powerful model organism for dissecting the neural circuitry underlying complex behaviours, from sensory perception to learning and memory. Drosophila can identify and remember visual features such as size, colour and contour orientation. However, the extent to which they use vision to recall specific locations remains unclear. Here we describe a visual place learning platform and demonstrate that Drosophila are capable of forming and retaining visual place memories to guide selective navigation. By targeted genetic silencing of small subsets of cells in the Drosophila brain, we show that neurons in the ellipsoid body, but not in the mushroom bodies, are necessary for visual place learning. Together, these studies reveal distinct neuroanatomical substrates for spatial versus non-spatial learning, and establish Drosophila as a powerful model for the study of spatial memories.
When the contrast of an image flickers as it moves, humans perceive an illusory reversal in the direction of motion. This classic illusion, called reverse-phi motion, has been well-characterized using psychophysics, and several models have been proposed to account for its effects. Here, we show that Drosophila melanogaster also respond behaviorally to the reverse-phi illusion and that the illusion is present in dendritic calcium signals of motion-sensitive neurons in the fly lobula plate. These results closely match the predictions of the predominant model of fly motion detection. However, high flicker rates cause an inversion of the reverse-phi behavioral response that is also present in calcium signals of lobula plate tangential cell dendrites but not predicted by the model. The fly’s behavioral and neural responses to the reverse-phi illusion reveal unexpected interactions between motion and flicker signals in the fly visual system and suggest that a similar correlation-based mechanism underlies visual motion detection across the animal kingdom.
We designed a real-time computer vision system, the Multi-Worm Tracker (MWT), which can simultaneously quantify the behavior of dozens of Caenorhabditis elegans on a Petri plate at video rates. We examined three traditional behavioral paradigms using this system: spontaneous movement on food, where the behavior changes over tens of minutes; chemotaxis, where turning events must be detected accurately to determine strategy; and habituation of response to tap, where the response is stochastic and changes over time. In each case, manual analysis or automated single-worm tracking would be tedious and time-consuming, but the MWT system allowed rapid quantification of behavior with minimal human effort. Thus, this system will enable large-scale forward and reverse genetic screens for complex behaviors.
We analyze the responses of human observers to an ensemble of monomolecular odorants. Each odorant is characterized by a set of 146 perceptual descriptors obtained from a database of odor character profiles. Each odorant is therefore represented by a point in a highly multidimensional sensory space. In this work we study the arrangement of odorants in this perceptual space. We argue that odorants densely sample a two-dimensional curved surface embedded in the multidimensional sensory space. This surface can account for more than half of the variance of the perceptual data. We also show that only 12% of experimental variance cannot be explained by curved surfaces of substantially small dimensionality (<10). We suggest that these curved manifolds represent the relevant spaces sampled by the human olfactory system, thereby providing surrogates for olfactory sensory space. For the case of 2D approximation, we relate the two parameters on the curved surface to the physico-chemical parameters of odorant molecules. We show that one of the dimensions is related to eigenvalues of molecules’ connectivity matrix, while the other is correlated with measures of molecules’ polarity. We discuss the behavioral significance of these findings.
Analyzing Drosophila melanogaster neural expression patterns in thousands of three-dimensional image stacks of individual brains requires registering them into a canonical framework based on a fiducial reference of neuropil morphology. Given a target brain labeled with predefined landmarks, the BrainAligner program automatically finds the corresponding landmarks in a subject brain and maps it to the coordinate system of the target brain via a deformable warp. Using a neuropil marker (the antibody nc82) as a reference of the brain morphology and a target brain that is itself a statistical average of data for 295 brains, we achieved a registration accuracy of 2 μm on average, permitting assessment of stereotypy, potential connectivity and functional mapping of the adult fruit fly brain. We used BrainAligner to generate an image pattern atlas of 2954 registered brains containing 470 different expression patterns that cover all the major compartments of the fly brain.
Gamma-aminobutyric acid (GABA) is the major inhibitory neurotransmitter in the mammalian brain. Once released, it is removed from the extracellular space by cellular uptake catalyzed by GABA transporter proteins. Four GABA transporters (GAT1, GAT2, GAT3 and BGT1) have been identified. Inhibition of the GAT1 by the clinically available anti-epileptic drug tiagabine has been an effective strategy for the treatment of some patients with partial seizures. Recently, the investigational drug EF1502, which inhibits both GAT1 and BGT1, was found to exert an anti-convulsant action synergistic to that of tiagabine, supposedly due to inhibition of BGT1. The present study addresses the role of BGT1 in seizure control and the effect of EF1502 by developing and exploring a new mouse line lacking exons 3-5 of the BGT1 (slc6a12) gene. The deletion of this sequence abolishes the expression of BGT1 mRNA. However, homozygous BGT1-deficient mice have normal development and show seizure susceptibility indistinguishable from that in wild-type mice in a variety of seizure threshold models including: corneal kindling, the minimal clonic and minimal tonic extension seizure threshold tests, the 6Hz seizure threshold test, and the i.v. pentylenetetrazol threshold test. We confirm that BGT1 mRNA is present in the brain, but find that the levels are several hundred times lower than those of GAT1 mRNA; possibly explaining the apparent lack of phenotype. In conclusion, the present results do not support a role for BGT1 in the control of seizure susceptibility and cannot provide a mechanistic understanding of the synergism that has been previously reported with tiagabine and EF1502.
Digital reconstruction of neurons from microscope images is an important and challenging problem in neuroscience. In this paper, we propose a model-based method to tackle this problem. We first formulate a model structure, then develop an algorithm for computing it by carefully taking into account morphological characteristics of neurons, as well as the image properties under typical imaging protocols. The method has been tested on the data sets used in the DIADEM competition and produced promising results for four out of the five data sets.
The formation of neuronal connections requires the precise guidance of developing axons toward their targets. In the Drosophila visual system, photoreceptor neurons (R cells) project from the eye into the brain. These cells are grouped into some 750 clusters comprised of eight photoreceptors or R cells each. R cells fall into three classes: R1 to R6, R7, and R8. Posterior R8 cells are the first to project axons into the brain. How these axons select a specific pathway is not known. Here, we used a microarray-based approach to identify genes expressed in R8 neurons as they extend into the brain. We found that Roundabout-3 (Robo3), an axon-guidance receptor, is expressed specifically and transiently in R8 growth cones. In wild-type animals, posterior-most R8 axons extend along a border of glial cells demarcated by the expression of Slit, the secreted ligand of Robo3. In contrast, robo3 mutant R8 axons extend across this border and fasciculate inappropriately with other axon tracts. We demonstrate that either Robo1 or Robo2 rescues the robo3 mutant phenotype when each is knocked into the endogenous robo3 locus separately, indicating that R8 does not require a function unique to the Robo3 paralog. However, persistent expression of Robo3 in R8 disrupts the layer-specific targeting of R8 growth cones. Thus, the transient cell-specific expression of Robo3 plays a crucial role in establishing neural circuits in the Drosophila visual system by selectively regulating pathway choice for posterior-most R8 growth cones.