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Bland, D.

Publications and source records attributed to Bland, D..

7 recordsLinked to original sources

Uncovering Sex Differences in the Drosophila Ventral Nerve Cord Through Connectome Alignment

There are now multiple Drosophila connectomes available, comprising both its brain and spinal cord - comparing these connectomes requires first classifying neurons into cell types. Existing approaches for cell typing typically require extensive manual curation. Here we present a new method that automatically aligns connectomes via network topology alone. Using two complete male ventral nerve cord (VNC) connectomes as references, we assign cell types to [~]13,000 neurons intrinsic to the female VNC, and automatically identify sex-specific and sexually dimorphic cell types. We not only provide a comprehensive census of cell types across male and female nerve cords, but we uncover connectivity differences that underlie differences in function. We focus on circuits underlying song production in males and oviposition behaviors in females, and investigate the counterparts of these circuits across sexes. Our automated methods and analyses provide insights into sex differences in circuits that connect the brain and body, and pave the way for comparative connectomics at scale.

neuroscience↗

Neuronal "parts list" and wiring diagram for a visual system

A catalog of neuronal cell types has often been called a "parts list" of the brain, and regarded as a prerequisite for understanding brain function. In the optic lobe of Drosophila, rules of connectivity between cell types have already proven essential for understanding fly vision. Here we analyze the fly connectome to complete the list of cell types intrinsic to the optic lobe, as well as the rules governing their connectivity. We more than double the list of known types. Most new cell types contain between 10 and 100 cells, and integrate information over medium distances in the visual field. Some existing type families (Tm, Li, and LPi) at least double in number of types. We introduce a new Sm interneuron family, which contains more types than any other, and three new families of cross-neuropil types. Self-consistency of cell types is demonstrated through automatic assignment of cells to types by distance in high-dimensional feature space, and further validation is provided by algorithms that select small subsets of discriminative features. Cell types with similar connectivity patterns divide into clusters that are interpretable in terms of motion, object, and color vision. Our work showcases the advantages of connectomic cell typing: complete and unbiased sampling, a rich array of features based on connectivity, and reduction of the connectome to a drastically simpler wiring diagram of cell types, with immediate relevance for brain function and development.

neuroscience↗

Neuronal wiring diagram of an adult brain

Connections between neurons can be mapped by acquiring and analyzing electron microscopic (EM) brain images. In recent years, this approach has been applied to chunks of brains to reconstruct local connectivity maps that are highly informative, yet inadequate for understanding brain function more globally. Here, we present the first neuronal wiring diagram of a whole adult brain, containing 5x107 chemical synapses between [~]130,000 neurons reconstructed from a female Drosophila melanogaster. The resource also incorporates annotations of cell classes and types, nerves, hemilineages, and predictions of neurotransmitter identities. Data products are available by download, programmatic access, and interactive browsing and made interoperable with other fly data resources. We show how to derive a projectome, a map of projections between regions, from the connectome. We demonstrate the tracing of synaptic pathways and the analysis of information flow from inputs (sensory and ascending neurons) to outputs (motor, endocrine, and descending neurons), across both hemispheres, and between the central brain and the optic lobes. Tracing from a subset of photoreceptors all the way to descending motor pathways illustrates how structure can uncover putative circuit mechanisms underlying sensorimotor behaviors. The technologies and open ecosystem of the FlyWire Consortium set the stage for future large-scale connectome projects in other species.

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Special Nuclear Layer Contacts Among Starburst Amacrine Cells in the Mouse Retina

We observed novel classes of cell-cell contacts between retinal starburst amacrine neurons, from finely detailed morphological reconstructions of cells from an electron microscopic image volume of a mouse retina. These contacts have peculiar morphological patterns and traits, different among the respective On and Off starburst amacrine subpopulations, but both occur within the soma layers as opposed to their regular laminae of contact within the inner plexiform layer.

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3D reconstruction of cell nuclei in a full Drosophila brain

We reconstructed all cell nuclei in a 3D image of a Drosophila brain acquired by serial section electron microscopy (EM). The total number of nuclei is approximately 133,000, at least 87% of which belong to neurons. Neuronal nuclei vary from several hundred down to roughly 5 cubic micrometers. Glial nuclei can be even smaller. The optic lobes contain more than two times the number of cells than the central brain. Our nuclear reconstruction serves as a spatial map and index to the cells in a Drosophila brain.

neuroscience↗

Modularity and neural coding from a brainstem synaptic wiring diagram

How much can connectomes with synaptic resolution help us understand brain function? An optimistic view is that a connectome is a major determinant of brain function and a key substrate for simulating a brain. Here we investigate the explanatory power of connectomics using a wiring diagram reconstructed from a larval zebrafish brainstem. We identify modules of strongly connected neurons that turn out to be specialized for different behavioral functions, the control of eye and body movements. We then build a neural network model using a synaptic weight matrix based on the reconstructed wiring diagram. This leads to predictions that statistically match the neural coding of eye position as observed by calcium imaging. Our work shows the promise of connectome-based brain modeling to yield experimentally testable predictions of neural activity and behavior, as well as mechanistic explanations of low-dimensional neural dynamics, a widely observed phenomenon in nervous systems.

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Structural and functional diversity of a dense sample of retinal ganglion cells

To aid understanding of retinal structure and function, we present as an online resource the dendritic arbors and visual responses of ganglion cells in a single patch of mouse retina. We divide the inner plexiform layer, which contains the dendritic arbors of ganglion cells, into four sublaminae defined by a purely anatomical principle of arbor segregation. The sublaminae serve as the starting point for a hierarchical clustering of our ganglion cells. We propose and apply a quantitative criterion for validating a cluster as a ganglion cell type: the aggregate neurite density of a type should be approximately uniform (\"density conservation\"). Finally, we find that ganglion cells arborizing in the inner marginal sublamina of the inner plexi-form layer exhibit significantly more sustained visual responses on average.

neuroscience↗