Publications by authors named "William Silversmith"

A long-standing goal in neuroscience is to understand how a circuit's form influences its function. Here, we reconstruct and analyze a synaptic wiring diagram of the larval zebrafish brainstem to predict key functional properties and validate them through comparison with physiological data. We identify modules of strongly connected neurons that turn out to be specialized for different behavioral functions, the control of eye and body movements.

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Serial section transmission electron microscopy (TEM) has proven to be one of the leading methods for millimeter-scale 3D imaging of brain tissues at nanoscale resolution. It is important to further improve imaging efficiency to acquire larger and more brain volumes. We report here a threefold increase in the speed of TEM by using a beam deflecting mechanism to enable highly efficient acquisition of multiple image tiles (nine) for each motion of the mechanical stage.

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Advances in Electron Microscopy, image segmentation and computational infrastructure have given rise to large-scale and richly annotated connectomic datasets which are increasingly shared across communities. To enable collaboration, users need to be able to concurrently create new annotations and correct errors in the automated segmentation by proofreading. In large datasets, every proofreading edit relabels cell identities of millions of voxels and thousands of annotations like synapses.

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Neuronal wiring diagrams reconstructed by electron microscopy pose new questions about the organization of nervous systems following the time-honored tradition of cross-species comparisons. The C. elegans connectome has been conceptualized as a sensorimotor circuit that is approximately feedforward, starting from sensory neurons proceeding to interneurons and ending with motor neurons.

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Article Synopsis
  • Understanding how circuit connectivity influences brain function is key to grasping brain computations, especially in the mouse primary visual cortex (V1), where similar-response neurons tend to be synaptically linked.
  • This study used a large dataset to show that neuronal connections are based not only within V1 but also span across different cortical layers and areas, indicating a 'like-to-like' connectivity rule throughout the visual system.
  • Additionally, a digital model revealed that neuronal response features, rather than their physical location, primarily predict synaptic connections, suggesting both basic and complex connectivity patterns that impact sensory processing and learning in both biological and artificial neural networks.
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We are now in the era of millimeter-scale electron microscopy (EM) volumes collected at nanometer resolution. Dense reconstruction of cellular compartments in these EM volumes has been enabled by recent advances in Machine Learning (ML). Automated segmentation methods produce exceptionally accurate reconstructions of cells, but post-hoc proofreading is still required to generate large connectomes free of merge and split errors.

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Starburst amacrine cells are a prominent neuron type in the mammalian retina that has been well-studied for its role in direction-selective information processing. One specific property of these cells is that their dendrites tightly stratify at specific depths within the inner plexiform layer (IPL), which, together with their unique expression of choline acetyltransferase (ChAT), has made them the most common depth marker for studying other retinal neurons in the IPL. This stratifying property makes it unexpected that they could routinely have dendrites reaching into the nuclear layer or that they could have somatic contact specializations, which is exactly what we have found in this study.

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Mammalian cortex features a vast diversity of neuronal cell types, each with characteristic anatomical, molecular and functional properties. Synaptic connectivity powerfully shapes how each cell type participates in the cortical circuit, but mapping connectivity rules at the resolution of distinct cell types remains difficult. Here, we used millimeter-scale volumetric electron microscopy to investigate the connectivity of all inhibitory neurons across a densely-segmented neuronal population of 1352 cells spanning all layers of mouse visual cortex, producing a wiring diagram of inhibitory connections with more than 70,000 synapses.

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Three-dimensional electron microscopy images of brain tissue and their dense segmentations are now petascale and growing. These volumes require the mass production of dense segmentation-derived neuron skeletons, multi-resolution meshes, image hierarchies (for both modalities) for visualization and analysis, and tools to manage the large amount of data. However, open tools for large-scale meshing, skeletonization, and data management have been missing.

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Neurons in the developing brain undergo extensive structural refinement as nascent circuits adopt their mature form. This physical transformation of neurons is facilitated by the engulfment and degradation of axonal branches and synapses by surrounding glial cells, including microglia and astrocytes. However, the small size of phagocytic organelles and the complex, highly ramified morphology of glia have made it difficult to define the contribution of these and other glial cell types to this crucial process.

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Learning from experience depends at least in part on changes in neuronal connections. We present the largest map of connectivity to date between cortical neurons of a defined type (layer 2/3 [L2/3] pyramidal cells in mouse primary visual cortex), which was enabled by automated analysis of serial section electron microscopy images with improved handling of image defects (250 × 140 × 90 μm volume). We used the map to identify constraints on the learning algorithms employed by the cortex.

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Article Synopsis
  • A semi-automated reconstruction of the L2/3 region of the mouse primary visual cortex was created using electron microscopy images, capturing various cell types and structures important for understanding visual processing.
  • The data includes visual response characteristics of pyramidal cells and is available for public access, along with interactive tools for analysis.
  • Research highlights how the organization of mitochondria and synapses relates to cell location, while predicting connectivity patterns in pyramidal cells correlates with their visual response strength and reliability.
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Article Synopsis
  • Advances in automated imaging now allow for the mapping of entire brains, with projects needing significant time for data proofreading due to their size.
  • FlyWire is introduced as an online platform that enables collaborative proofreading of neural circuits in fruit flies, utilizing 3D interactive tools for efficient editing from anywhere.
  • The platform encourages community participation, enhances data accuracy, and promotes faster scientific discoveries, showcased through the analysis of mechanosensory neurons' connectome.
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Inhibitory neurons in mammalian cortex exhibit diverse physiological, morphological, molecular, and connectivity signatures. While considerable work has measured the average connectivity of several interneuron classes, there remains a fundamental lack of understanding of the connectivity distribution of distinct inhibitory cell types with synaptic resolution, how it relates to properties of target cells, and how it affects function. Here, we used large-scale electron microscopy and functional imaging to address these questions for chandelier cells in layer 2/3 of the mouse visual cortex.

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Sustained changes in mood or action require persistent changes in neural activity, but it has been difficult to identify the neural circuit mechanisms that underlie persistent activity and contribute to long-lasting changes in behavior. Here, we show that a subset of Doublesex+ pC1 neurons in the female brain, called pC1d/e, can drive minutes-long changes in female behavior in the presence of males. Using automated reconstruction of a volume electron microscopic (EM) image of the female brain, we map all inputs and outputs to both pC1d and pC1e.

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As acquiring bigger data becomes easier in experimental brain science, computational and statistical brain science must achieve similar advances to fully capitalize on these data. Tackling these problems will benefit from a more explicit and concerted effort to work together. Specifically, brain science can be further democratized by harnessing the power of community-driven tools, which both are built by and benefit from many different people with different backgrounds and expertise.

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Scientific software is often developed with scientists in mind, resulting in complex tools with a steep learning curve. , however, are designed for scientists- members of the general public. These games maintain scientific accuracy while placing design goals such as usability and enjoyment at the forefront.

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Article Synopsis
  • A new digital resource showcases nearly 400 ganglion cells from a mouse retina, allowing users to explore their 3D structures and visual responses interactively.
  • The study identifies key principles in the retina's inner plexiform layer: an arbor segregation principle related to light orientation and a density conservation principle in horizontal structure.
  • The findings indicate that the anatomical positioning of ganglion cells affects their visual response characteristics, suggesting potential applications for similar methods in mapping neuronal structures and functions elsewhere in the nervous system.
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