Jump to Content

Laramie Leavitt

Research Areas

Authored Publications
Google Publications
Other Publications
Sort By
  • Title
  • Title, descending
  • Year
  • Year, descending
    A connectomic study of a petascale fragment of human cerebral cortex
    Alex Shapson-Coe
    Daniel R. Berger
    Yuelong Wu
    Richard L. Schalek
    Shuohong Wang
    Neha Karlupia
    Sven Dorkenwald
    Evelina Sjostedt
    Dongil Lee
    Luke Bailey
    Angerica Fitzmaurice
    Rohin Kar
    Benjamin Field
    Hank Wu
    Julian Wagner-Carena
    David Aley
    Joanna Lau
    Zudi Lin
    Donglai Wei
    Hanspeter Pfister
    Adi Peleg
    Jeff W. Lichtman
    bioRxiv (2021)
    Preview abstract We acquired a rapidly preserved human surgical sample from the temporal lobe of the cerebral cortex. We stained a 1 mm3 volume with heavy metals, embedded it in resin, cut more than 5000 slices at ∼30 nm and imaged these sections using a high-speed multibeam scanning electron microscope. We used computational methods to render the three-dimensional structure containing 57,216 cells, hundreds of millions of neurites and 133.7 million synaptic connections. The 1.4 petabyte electron microscopy volume, the segmented cells, cell parts, blood vessels, myelin, inhibitory and excitatory synapses, and 104 manually proofread cells are available to peruse online. Many interesting and unusual features were evident in this dataset. Glia outnumbered neurons 2:1 and oligodendrocytes were the most common cell type in the volume. Excitatory spiny neurons comprised 69% of the neuronal population, and excitatory synapses also were in the majority (76%). The synaptic drive onto spiny neurons was biased more strongly toward excitation (70%) than was the case for inhibitory interneurons (48%). Despite incompleteness of the automated segmentation caused by split and merge errors, we could automatically generate (and then validate) connections between most of the excitatory and inhibitory neuron types both within and between layers. In studying these neurons we found that deep layer excitatory cell types can be classified into new subsets, based on structural and connectivity differences, and that chandelier interneurons not only innervate excitatory neuron initial segments as previously described, but also each other’s initial segments. Furthermore, among the thousands of weak connections established on each neuron, there exist rarer highly powerful axonal inputs that establish multi-synaptic contacts (up to ∼20 synapses) with target neurons. Our analysis indicates that these strong inputs are specific, and allow small numbers of axons to have an outsized role in the activity of some of their postsynaptic partners. View details
    A connectome and analysis of the adult Drosophila central brain
    Sean M Ryan
    Megan Sammons
    Anne K Scott
    Ashley L Scott
    Aya Shinomiya
    Claire Smith
    Kelsey Smith
    Natalie L Smith
    Margaret A Sobeski
    Alia Suleiman
    Jackie Swift
    Satoko Takemura
    Iris Talebi
    Dorota Tarnogorska
    Emily Tenshaw
    Temour Tokhi
    John J Walsh
    Tansy Yang
    Jane Anne Horne
    Feng Li
    Ruchi Parekh
    Patricia K Rivlin
    Vivek Jayaraman
    Marta Costa
    Gregory SXE Jefferis
    Kei Ito
    Stephan Saalfeld
    Reed George
    Ian Meinertzhagen
    Gerald M Rubin
    Harald F Hess
    Stephen M Plaza
    Louis K Scheffer
    C Shan Xu
    Zhiyuan Lu
    Shin-ya Takemura
    Kenneth J Hayworth
    Gary B Huang
    Kazunori Shinomiya
    Stuart Berg
    Jody Clements
    Philip M Hubbard
    William T Katz
    Lowell Umayam
    Ting Zhao
    David Ackerman
    John Bogovic
    Tom Dolafi
    Dagmar Kainmueller
    Takashi Kawase
    Khaled A Khairy
    Larry Lindsey
    Nicole Neubarth
    Donald J Olbris
    Hideo Otsuna
    Eric T Trautman
    Masayoshi Ito
    Alexander S Bates
    Jens Goldammer
    Tanya Wolff
    Robert Svirskas
    Philipp Schlegel
    Erika Neace
    Christopher J Knecht
    Chelsea X Alvarado
    Dennis A Bailey
    Samantha Ballinger
    Jolanta A Borycz
    Brandon S Canino
    Natasha Cheatham
    Michael Cook
    Marisa Dreher
    Octave Duclos
    Bryon Eubanks
    Kelli Fairbanks
    Samantha Finley
    Nora Forknall
    Audrey Francis
    Gary Patrick Hopkins
    Emily M Joyce
    SungJin Kim
    Nicole A Kirk
    Julie Kovalyak
    Shirley Lauchie
    Alanna Lohff
    Charli Maldonado
    Emily A Manley
    Sari McLin
    Caroline Mooney
    Miatta Ndama
    Omotara Ogundeyi
    Nneoma Okeoma
    Christopher Ordish
    Nicholas Padilla
    Christopher M Patrick
    Tyler Paterson
    Elliott E Phillips
    Emily M Phillips
    Neha Rampally
    Caitlin Ribeiro
    Madelaine K Robertson
    Jon Thomson Rymer
    eLife, vol. 9 (2020)
    Preview abstract The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly's brain. View details
    Preview abstract Reconstruction of neural circuitry at single-synapse resolution is an attractive target for improving understanding of the nervous system in health and disease. Serial section transmission electron microscopy (ssTEM) is among the most prolific imaging methods employed in pursuit of such reconstructions. We demonstrate how Flood-Filling Networks (FFNs) can be used to computationally segment a forty-teravoxel whole-brain Drosophila ssTEM volume. To compensate for data irregularities and imperfect global alignment, FFNs were combined with procedures that locally re-align serial sections as well as dynamically adjust and synthesize image content. The proposed approach produced a largely merger-free segmentation of the entire ssTEM Drosophila brain, which we make freely available. As compared to manual tracing using an efficient skeletonization strategy, the segmentation enabled circuit reconstruction and analysis workflows that were an order of magnitude faster. View details
    No Results Found