Allen Brain Observatory - Visual Coding AWS Public Data Set

electrophysiology image processing life sciences machine learning Mus musculus neurobiology neuroimaging signal processing

Description

The Allen Brain Observatory – Visual Coding is a large-scale, standardized survey of physiological activity across the mouse visual cortex, hippocampus, and thalamus. It includes datasets collected with both two-photon imaging and Neuropixels probes, two complementary techniques for measuring the activity of neurons in vivo. The two-photon imaging dataset features visually evoked calcium responses from GCaMP6-expressing neurons in a range of cortical layers, visual areas, and Cre lines. The Neuropixels dataset features spiking activity from distributed cortical and subcortical brain regions, collected under analogous conditions to the two-photon imaging experiments. We hope that experimentalists and modelers will use these comprehensive, open datasets as a testbed for theories of visual information processing.

Update Frequency

Annually

License

http://www.alleninstitute.org/legal/terms-use/

Documentation

https://github.com/AllenInstitute/AllenSDK/wiki/Use-the-Allen-Brain-Observatory-%E2%80%93-Visual-Coding-on-AWS

Managed By

Allen Institute

See all datasets managed by Allen Institute.

Contact

awspublicdataset@alleninstitute.org

Usage Examples

Tutorials

Resources on AWS

  • Description
    Project data files in a public bucket
    Resource type
    S3 Bucket
    Amazon Resource Name (ARN)
    arn:aws:s3:::allen-brain-observatory
    AWS Region
    us-west-2
    AWS CLI Access (No AWS account required)
    aws s3 ls s3://allen-brain-observatory/ --no-sign-request
  • Description
    SageMaker launch template with s3fs bucket mounts
    Resource type
    S3 Bucket
    Amazon Resource Name (ARN)
    arn:aws:s3:::allen-brain-observatory-templates
    AWS Region
    us-west-2
    AWS CLI Access (No AWS account required)
    aws s3 ls s3://allen-brain-observatory-templates/ --no-sign-request

Edit this dataset entry on GitHub

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