Mojo is an interactive proofreading tool for annotation of 3D EM data.

## Kasthuri et al. (2015)

Bobby Kasthuri, Ph.D. under the tutelage of Jeff Lichtman, M.D., Ph.D., acquired a data set from mouse cortex with a 3x3x30 cubic nanometer spatial resolution, yielding 660GB of images. This beautiful data was published Friday, July 30th 2015 in Cell.

We describe automated technologies to probe the structure of neural tissue at nanometer resolution and use them to generate a saturated reconstruction of a sub-volume of mouse neocortex in which all cellular objects (axons, dendrites, and glia) and many sub-cellular components (synapses, synaptic vesicles, spines, spine apparati, postsynaptic densities, and mitochondria) are rendered and itemized in a database. We explore these data to study physical properties of brain tissue. For example, by tracing the trajectories of all excitatory axons and noting their juxtapositions, both synaptic and non-synaptic, with every dendritic spine we refute the idea that physical proximity is sufficient to predict synaptic connectivity (the so-called Peters’ rule). This online minable database provides general access to the intrinsic complexity of the neocortex and enables further data-driven inquiries.

Learn More#### Data

#### kasthuri11

###### Example cutout

# pip install numpy tifffile cloud-volume import numpy as np import tifffile from cloudvolume import CloudVolume vol = CloudVolume( "s3://open-neurodata/kasthuri/kasthuri11/image", mip=0, use_https=True ) # load data into numpy array cutout = vol[11264:11776, 13312:13824, 912:928] # save cutout as TIFF tifffile.imwrite("data.tiff", data=np.transpose(cutout))

Documentation for *cloud-volume* located here

#### kasthuri14Maine

###### Example cutout

# pip install numpy tifffile cloud-volume import numpy as np import tifffile from cloudvolume import CloudVolume vol = CloudVolume( "s3://open-neurodata/kasthuri/kasthuri14Maine/image", mip=0, use_https=True ) # load data into numpy array cutout = vol[2560:3072, 3072:3584, 1184:1200] # save cutout as TIFF tifffile.imwrite("data.tiff", data=np.transpose(cutout))

Documentation for *cloud-volume* located here

#### kasthuri14s1colEM

###### Example cutout

# pip install numpy tifffile cloud-volume import numpy as np import tifffile from cloudvolume import CloudVolume vol = CloudVolume( "s3://open-neurodata/kasthuri/kasthuri14s1colEM/image", mip=0, use_https=True ) # load data into numpy array cutout = vol[28672:29184, 15872:16384, 112:128] # save cutout as TIFF tifffile.imwrite("data.tiff", data=np.transpose(cutout))

Documentation for *cloud-volume* located here

#### Publications

N. Kasthuri, K. J. Hayworth, D. R. Berger, R. L. Schalek, J. A. Conchello, S. Knowles-Barley, D. Lee, A. Vázquez-Reina, V. Kaynig, T. R. Jones, M. Roberts, J. L. Morgan, J. C. Tapia, H. S. Seung, W. G. Roncal, J. T. Vogelstein, R. Burns, D. L. Sussman, C. E. Priebe, H. Pfister, and J. W. Lichtman. Saturated Reconstruction of a Volume of Neocortex. *Cell*, 2015.

To access this data, please view the guide.

Data on this site are licensed under a ODC-By v1.0 license.