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The neuronal architecture of the mushroom body provides a logic for associative learning

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      Abstract

      We identified the neurons comprising the Drosophila mushroom body (MB), an associative center in invertebrate brains, and provide a comprehensive map describing their potential connections. Each of the 21 MB output neuron (MBON) types elaborates segregated dendritic arbors along the parallel axons of ∼2000 Kenyon cells, forming 15 compartments that collectively tile the MB lobes. MBON axons project to five discrete neuropils outside of the MB and three MBON types form a feedforward network in the lobes. Each of the 20 dopaminergic neuron (DAN) types projects axons to one, or at most two, of the MBON compartments. Convergence of DAN axons on compartmentalized Kenyon cell–MBON synapses creates a highly ordered unit that can support learning to impose valence on sensory representations. The elucidation of the complement of neurons of the MB provides a comprehensive anatomical substrate from which one can infer a functional logic of associative olfactory learning and memory.

      DOI: http://dx.doi.org/10.7554/eLife.04577.001

      eLife digest

      One of the key goals of neuroscience is to understand how specific circuits of brain cells enable animals to respond optimally to the constantly changing world around them. Such processes are more easily studied in simpler brains, and the fruit fly—with its small size, short life cycle, and well-developed genetic toolkit—is widely used to study the genes and circuits that underlie learning and behavior.

      Fruit flies can learn to approach odors that have previously been paired with food, and also to avoid any odors that have been paired with an electric shock, and a part of the brain called the mushroom body has a central role in this process. When odorant molecules bind to receptors on the fly's antennae, they activate neurons in the antennal lobe of the brain, which in turn activate cells called Kenyon cells within the mushroom body. The Kenyon cells then activate output neurons that convey signals to other parts of the brain.

      It is known that relatively few Kenyon cells are activated by any given odor. Moreover, it seems that a given odor activates different sets of Kenyon cells in different flies. Because the association between an odor and the Kenyon cells it activates is unique to each fly, each fly needs to learn through its own experiences what a particular pattern of Kenyon cell activation means.

      Aso et al. have now applied sophisticated molecular genetic and anatomical techniques to thousands of different transgenic flies to identify the neurons of the mushroom body. The resulting map reveals that the mushroom body contains roughly 2200 neurons, including seven types of Kenyon cells and 21 types of output cells, as well as 20 types of neurons that use the neurotransmitter dopamine. Moreover, this map provides insights into the circuits that support odor-based learning. It reveals, for example, that the mushroom body can be divided into 15 anatomical compartments that are each defined by the presence of a specific set of output and dopaminergic neuron cell types. Since the dopaminergic neurons help to shape a fly's response to odors on the basis of previous experience, this organization suggests that these compartments may be semi-autonomous information processing units.

      In contrast to the rest of the insect brain, the mushroom body has a flexible organization that is similar to that of the mammalian brain. Elucidating the circuits that support associative learning in fruit flies should therefore make it easier to identify the equivalent mechanisms in vertebrate animals.

      DOI: http://dx.doi.org/10.7554/eLife.04577.002

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      Most cited references 116

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      One of the most challenging problems in modern neuroimaging is detailed characterization of neurodegeneration. Quantifying spatial and longitudinal atrophy patterns is an important component of this process. These spatiotemporal signals will aid in discriminating between related diseases, such as frontotemporal dementia (FTD) and Alzheimer's disease (AD), which manifest themselves in the same at-risk population. Here, we develop a novel symmetric image normalization method (SyN) for maximizing the cross-correlation within the space of diffeomorphic maps and provide the Euler-Lagrange equations necessary for this optimization. We then turn to a careful evaluation of our method. Our evaluation uses gold standard, human cortical segmentation to contrast SyN's performance with a related elastic method and with the standard ITK implementation of Thirion's Demons algorithm. The new method compares favorably with both approaches, in particular when the distance between the template brain and the target brain is large. We then report the correlation of volumes gained by algorithmic cortical labelings of FTD and control subjects with those gained by the manual rater. This comparison shows that, of the three methods tested, SyN's volume measurements are the most strongly correlated with volume measurements gained by expert labeling. This study indicates that SyN, with cross-correlation, is a reliable method for normalizing and making anatomical measurements in volumetric MRI of patients and at-risk elderly individuals.
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        We established a collection of 7,000 transgenic lines of Drosophila melanogaster. Expression of GAL4 in each line is controlled by a different, defined fragment of genomic DNA that serves as a transcriptional enhancer. We used confocal microscopy of dissected nervous systems to determine the expression patterns driven by each fragment in the adult brain and ventral nerve cord. We present image data on 6,650 lines. Using both manual and machine-assisted annotation, we describe the expression patterns in the most useful lines. We illustrate the utility of these data for identifying novel neuronal cell types, revealing brain asymmetry, and describing the nature and extent of neuronal shape stereotypy. The GAL4 lines allow expression of exogenous genes in distinct, small subsets of the adult nervous system. The set of DNA fragments, each driving a documented expression pattern, will facilitate the generation of additional constructs for manipulating neuronal function. Copyright © 2012 The Authors. Published by Elsevier Inc. All rights reserved.
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          We report a photoactivatable variant of the Aequorea victoria green fluorescent protein (GFP) that, after intense irradiation with 413-nanometer light, increases fluorescence 100 times when excited by 488-nanometer light and remains stable for days under aerobic conditions. These characteristics offer a new tool for exploring intracellular protein dynamics by tracking photoactivated molecules that are the only visible GFPs in the cell. Here, we use the photoactivatable GFP both as a free protein to measure protein diffusion across the nuclear envelope and as a chimera with a lysosomal membrane protein to demonstrate rapid interlysosomal membrane exchange.
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            Author and article information

            Affiliations
            [1 ]Janelia Research Campus, Howard Hughes Medical Institute , Ashburn, United States
            [2 ]Howard Hughes Medical Institute, Columbia University , New York, United States
            [3 ]deptDepartment of Neuroscience, College of Physicians and Surgeons , Columbia University , New York, United States
            [4 ]deptDepartment of Physiology and Cellular Biophysics, College of Physicians and Surgeons , Columbia University , New York, United States
            [5 ]Tohuku University Graduate School of Life Sciences , Sendai, Japan
            [6 ]Max-Planck Institute of Neurobiology , Martinsried, Germany
            [7 ]deptDepartment of Biochemistry and Molecular Biophysics, College of Physicians and Surgeons , Columbia University , New York, United States
            Brandeis University , United States
            Brandeis University , United States
            Author notes
            Contributors
            Role: Reviewing editor,
            Brandeis University , United States
            Journal
            eLife
            eLife
            eLife
            eLife
            eLife Sciences Publications, Ltd
            2050-084X
            2050-084X
            23 December 2014
            2014
            : 3
            25535793 4273437 04577 10.7554/eLife.04577
            © 2014, Aso et al

            This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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            Funding
            Funded by: FundRef http://dx.doi.org/10.13039/100000011, universityHoward Hughes Medical Institute;
            Award Recipient :
            Funded by: FundRef http://dx.doi.org/10.13039/100000011, universityHoward Hughes Medical Institute;
            Award ID: Janelia Visiting Scientist Program
            Award Recipient :
            Funded by: FundRef http://dx.doi.org/10.13039/501100000324, Gatsby Charitable Foundation;
            Award ID: Gatsby Initiative Fund in Brain Circuitry at Columbia University
            Award Recipient :
            Funded by: Swartz Foundation;
            Award Recipient :
            Funded by: FundRef http://dx.doi.org/10.13039/501100002347, Bundesministerium für Bildung und Forschung;
            Award ID: Bernstein Focus Neurobiology of Learning 01GQ0932
            Award Recipient :
            Funded by: FundRef http://dx.doi.org/10.13039/501100004189, Max-Planck-Gesellschaft;
            Award Recipient :
            Funded by: FundRef http://dx.doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft;
            Award ID: TA 552/5-1
            Award Recipient :
            Funded by: FundRef http://dx.doi.org/10.13039/501100001691, Japan Society for the Promotion of Science;
            Award ID: MEXT/JSPS KAKENHI 25890003, 26120705, 26119503 and 26250001
            Award Recipient :
            Funded by: FundRef http://dx.doi.org/10.13039/100007428, Naito Foundation;
            Award Recipient :
            Funded by: FundRef http://dx.doi.org/10.13039/100001033, Jane Coffin Childs Memorial Fund for Medical Research;
            Award Recipient :
            Funded by: FundRef http://dx.doi.org/10.13039/100001229, G Harold and Leila Y. Mathers Foundation;
            Award Recipient :
            Funded by: FundRef http://dx.doi.org/10.13039/100000893, Simons Foundation;
            Award Recipient :
            The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
            Categories
            Research Article
            Neuroscience
            Custom metadata
            2.0
            A map of the entire array of cell types and potential projections in the mushroom body of the fruit fly brain provides insights into the circuitry that supports learning of stimulus-reward and stimulus–punishment associations.

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