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Development and Function of Drosophila Visual Circuits

Chi-Hon Lee, MD, PhD
  • Chi-Hon Lee, MD, PhD, Head, Section on Neuronal Connectivity
  • Chun-Yuan Ting, PhD, Research Fellow
  • Tzu-Yang Lin, PhD, Postdoctoral Fellow
  • Krishna Melnattur, PhD, Postdoctoral Fellow
  • Thangavel Karuppudurai, PhD, Postdoctoral Fellow
  • Mingmin Zhou, PhD, Postdoctoral Fellow
  • Moyi Li, BA, Biological Laboratory Technician

Using the Drosophila visual system as a model, we study how neurons form complex yet stereotyped synaptic connections during development and how the assembled neural circuits extract various visual attributes (such as color and motion) to guide animal behaviors. Flies' vision is mediated by three types of photoreceptors, R1-6, R7, and R8, which each respond to a specific spectrum of light. The three types of photoreceptors project their axons to three distinct layers in the brain, where the cells form synaptic connections with different target neurons. To study visual circuit functions, we combined structural and functional approaches to map visual circuits. Using both light- and electron-microscopy studies, we identified the medulla neurons that are post-synaptic to photoreceptors. We determined their usage of neurotransmitters and receptors by single-cell transcript profiling. Using behavioral assays, we are examining the roles of these medulla neurons in processing motion and color information. For circuit development, we focus on the medulla neurons that receive direct inputs from R7 and R8 photoreceptors, and we examine the role of Activin signaling in the neurons' dendritic development.

Dendritic development of Drosophila optic lobe neurons

Our long-term goal is to determine how visual circuits are assembled during development. Most regions of vertebrate and invertebrate brains are organized in columns and layers, which facilitate information processing and propagating. During development, axons and dendrites are routed to specific layers and columns. Spatial coincidence of axons and dendrites affords a key specificity determinant for synaptic pairing. While much has been discovered about axonal guidance in the past years, essentially nothing is known about how target neurons extend dendrites in type-specific patterns to pair with photoreceptor pre-synaptic terminals. Much of our current understandings of dendrite development came from the studies of Drosophila Da neurons in the peripheral nervous system, which extend dendrites not to specific targets but to populate (or tiling) a two-dimensional receptive field. Two key questions concerning dendritic development remain largely unanswered: how CNS neurons establish type-specific dendritic arborization patterns in three-dimensional space and how synaptic partnership between axons and dendrites are matched.

Using the Drosophila optic lobe neurons as a model, we aim to determine the molecular mechanisms by which transmedulla (Tm) neurons extend dendrites to specific layers and columns to match with photoreceptor presynaptic terminals. Like the vertebrate cortex and retina, the medulla neuropil is organized in columns and layers, suggesting that the fly medulla neurons and vertebrate cortex neurons confront similar challenges in routing their dendrites to specific layers and columns. In addition, the fly visual system has several unique advantages: (i) the medulla neurons extend dendritic arbors in a three-dimensional lattice structure, facilitating morphometric analysis; (ii) the presynaptic targets for many medulla neuron types are known from our anatomical studies; (iii) genetic tools for labeling specific classes of medulla neurons and determining their connectivity have been developed.

We developed new techniques to analyze dendritic structures three-dimensionally and to exploit the unique advantages of this system. First, to image reliably the slender dendrites of medulla neurons, we developed a dual-view imaging technique that generates isotropic 3D-images of dendrites. Second, we developed an image registration technique that makes use of the regular array structures of the optic lobe to standardize dendritic branching patterns. This, in combination with a series of statistical methods we established, allows us to analyze dendritic patterns in three-dimensionally. Third, we established an imaging technique (GRASP) to detect synaptic contacts at the light-microscopic level. We used these techniques to generate a data set of three types of medulla neurons. Our preliminary analyses suggested (i) that the medulla neurons exhibit stereotypic dendritic arbors but that the detailed branching pattern and topology are not conserved; (ii) that the synaptic partnership between axons and dendrites are robust and specific. Based on these results, we hypothesize that dendritic development in the optic lobe neurons proceed in two distinct processes: (i) routing dendrites in type-specific fashion, which, at least in part, serves to maximize the possibility of finding appropriate synaptic partners; (ii) matching different sections of dendrites with specific afferents, which likely requires specific interactions between axons and dendrites to ensure synaptic specificity.

To determine the molecular mechanisms that govern dendritic routing, we took a candidate approach and examined a series of available mutants. Our previous study revealed that R7 and R8 photoreceptor axons express Activin, which could potentially signal the medulla Tm neurons in the antegrade fashion, in addition to its known autocrine-signaling role in R7s. We found that Activin signaling is required cell-autonomously in two R7/8 synaptic target neurons, Dm8 and Tm20, for appropriate dendritic patterning. Using the imaging and statistical analysis tools we developed, we characterized the loss-of-function mutant phenotypes and found that Activin signaling appears to have distinct effects on dendritic patterning of Tm20 and Dm8. Removing the Activin receptor Baboon in single Tm20 neurons resulted in reduced sizes of the dendritic trees as well as lower total number of branches (about a 50% reduction) and diminished branching probability, leading to dendrites of low complexity. In contrast, baboon mutant Dm8 neurons have expanded dendritic fields but reduced complexity of dendritic trees. We are now determining the signaling pathways by which Activin regulates dendritic development in Dm8 and Tm20 neurons.

Mapping color-vision circuits

Our goal is to understand how visual systems extract spectral information to generate color perception. We use the fly visual system as a model to study color vision. The fly's R1–6, R7, and R8 photoreceptors each connect to a distinct set of neurons in the peripheral optic lobes, the lamina, and medulla. By systematically "inactivating" or "restoring" the function of specific neuronal types and examining the behavioral consequences, we are determining the role of these medulla neurons in processing color information.

Using both light- and electron-microscopy, we determined the synaptic circuits of the photoreceptors and their synaptic target neurons in the medulla. The chromatic photoreceptors R7 and R8 provide inputs to a subset of first-order interneurons, which likely serve as color opponent neurons. The first-order interneurons Tm5a/b/c receive direct synaptic inputs from R7, while Tm9, Tm20, and Tm5c receive inputs from R8. In addition, these Tm neurons receive indirect inputs from R1–6 via L3 and relay spectral information from the medulla to various lobula layers. In addition, the amacrine neuron Dm8 receives input from multiple R7s and provides input for Tm5. Functional studies further revealed that the amacrine Dm8 neurons are both required and sufficient for animals' innate spectral preference for UV light, while Tm9 neurons are sufficient to drive green phototaxis.

To relate neural connectivity to functions, we determined the components of the neural computation machinery expressed in the neurons of interest. In particular, the use of neurotransmitters and receptors provides crucial information about the polarity and dynamics of signal transmission. We found that promoter constructs are not reliable reporters so instead developed a single-cell transcript profiling method, which directly probes the expression of neuronal transmitter synthesis enzymes, transporters, and receptors. This RT–PCR based method is capable of assaying maximally 20 genes from a single GFP-labeled neuron, and the detection sensitivity is 3–10 transcript copies. As a proof of principle, we determined the expression of all known acetylcholine receptors in three cholinergic neurons, L2, L4, and Tm2, which interconnect with one another and mediate motion detection. We found that these neurons express type-invariant subsets of nicotinic receptors. With color-vision circuit, we determined that L3, Tm9, Tm5c, and Dm8 neurons are glutamatergic. As a proof of principle, we knocked down the vesicular glutamate transporter (vGlut) in the Dm8 neurons and found that reducing vGlut level in Dm8 leads to aberrant green preference, phenocopying shits–mediated (shits is a thermo-sensitive form of dynamin) inactivation of Dm8. We are now applying this approach to different Tm neurons and determining their requirement of transmitter and receptors. This information will provide critical information for determining the logic of information transmission and color computation.


  • Lee, C-H. The split view of motion. Nature 2010;486:178-179.
  • Ting C-Y, Gu S, Guttikonda S, Lin T-Y, White BH, Lee C-H. Focusing transgene expression in Drosophila by coupling Gal4 with a novel split-LexA expression system. Genetics 2010;188:229-233.
  • Melnattur KV, Lee C-H. Visual circuit assembly in Drosophila. Dev Neurobiol 2011;in press.
  • Brody T, Yavatkar AS, Kuzin A, Tyson L, Kundu M, Ross J, Lin T-Z, Lee C-H, Awasaki T, Lee T, Odenwald WF. Use of a Drosophila genome-wide conserved sequence database to identify functionally related cis-regulatory enhancers. Dev Dyn 2011;in press.


  • Matthew McAuliffe, PhD, Division of Biomedical Imaging Research Services Section, CIT, NIH, Bethesda, MD
  • Philip McQueen, PhD, Mathematical and Statistical Computing Laboratory, CIT, NIH, Bethesda, MD
  • Ian Meinertzhagen, PhD, DSc, Dalhousie University, Halifax, Canada
  • Nishith Pandya, BA, Division of Biomedical Imaging Research Services Section, CIT, NIH, Bethesda, MD
  • Thomas Pohida, MSEE, Division of Computational Bioscience, CIT, NIH, Bethesda, MD
  • Randy Pursley, MSEE, Division of Computational Bioscience, CIT, NIH, Bethesda, MD
  • Mihaela Serpe, PhD, Program in Cellular Regulation and Metabolism, NICHD, Bethesda, MD
  • Paul Smith, PhD, Laboratory of Bioengineering and Physical Science, NIBIB, NIH, Bethesda, MD
  • Mark Stopfer, PhD, Program in Developmental Neuroscience, NICHD, Bethesda, MD
  • Benjamin White, PhD, Laboratory of Molecular Biology, NIMH, Bethesda, MD

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