Welcome to the Allen SDK

The Allen Software Development Kit houses source code for reading and processing Allen Brain Atlas data. The Allen SDK focuses on the Allen Brain Observatory, Cell Types Database, and Mouse Brain Connectivity Atlas.

Attention

As of October 2019, we have dropped Python 2 support and any files with a py2 dependency (for example analysis files) have been updated.

_static/sdk_cam.png

Allen Brain Observatory

The Allen Brain Observatory is a data resource for understanding sensory processing in the mouse visual cortex. This study systematically measures visual responses in multiple cortical areas and layers using two-photon calcium imaging of GCaMP6-labeled neurons targeted using Cre driver lines. Response characterizations include orientation tuning, spatial and temporal frequency tuning, temporal dynamics, and spatial receptive field structure.

The mean fluorescence traces for all segmented cells are available in the Neurodata Without Borders file format (NWB files). These files contain standardized descriptions of visual stimuli to support stimulus-specific tuning analysis. The Allen SDK provides code to:

  • download and organize experiment data according to cortical area, imaging depth, and Cre line
  • remove the contribution of neuropil signal from fluorescence traces
  • access (or compute) dF/F traces based on the neuropil-corrected traces
  • perform stimulus-specific tuning analysis (e.g. drifting grating direction tuning)

_static/ccf_v3_sdk.png

Allen Cell Types Database

The Allen Cell Types Database contains electrophysiological and morphological characterizations of individual neurons in the mouse primary visual cortex. The Allen SDK provides Python code for accessing electrophysiology measurements (NWB files) for all neurons and morphological reconstructions (SWC files) for a subset of neurons.

The Database also contains two classes of models fit to this data set: biophysical models produced using the NEURON simulator and generalized leaky integrate and fire models (GLIFs) produced using custom Python code provided with this toolkit.

The Allen SDK provides sample code demonstrating how to download neuronal model parameters from the Allen Brain Atlas API and run your own simulations using stimuli from the Allen Cell Types Database or custom current injections:


_static/connectivity.png

Allen Mouse Brain Connectivity Atlas

The Allen Mouse Brain Connectivity Atlas is a high-resolution map of neural connections in the mouse brain. Built on an array of transgenic mice genetically engineered to target specific cell types, the Atlas comprises a unique compendium of projections from selected neuronal populations throughout the brain. The primary data of the Atlas consists of high-resolution images of axonal projections targeting different anatomic regions or various cell types using Cre-dependent specimens. Each data set is processed through an informatics data analysis pipeline to obtain spatially mapped quantified projection information.

The Allen SDK provides Python code for accessing experimental metadata along with projection signal volumes registered to a common coordinate framework. This framework has structural annotations, which allows users to compute structure-level signal statistics.

See the mouse connectivity section for more details.

What’s New - 1.3.0 (December 12, 2019)

The 1.3.0 release adds

  • Improved Neuropixels data download performance by enabling asynchronous transfers. Users can now also specify a timeout and number of retries when downloading data.

and fixes

  • Hanging downloads for Neuropixels NWB files
  • Updated AllenSDK readme and contributing documentation

What’s New - 1.2.0 (November 21, 2019)

The 1.2.0 release adds

  • (internal feature) A project cache for the Behavior Ophys project, with example notebook
  • (internal feature) A major overhaul of the BehaviorOphysLimsApi
  • (internal feature) Updates to the EcephysProjectLimsApi such that it returns data in the same format as the EcephyProjectWarehouseApi
  • improved eye-tracking area calculation

and fixes

  • several flaky tests
  • regress tests which depend on scipy’s ks_2samp
  • (internal feature) duplicate caching on the Bevavior Ophys Lims Api