This code processes light-sheet data in several steps:
- parsing behavior/stimulus time series into 3 regressors,
- preprocessing imaging stacks: rigid registration and correction for XY drift,
- computing functional maps by linear regression,
- saving the functional maps.
The code can be executed as Python Jupyter notebooks, using a personal computer or a cluster. Two downsampled datasets are provided in raw.zip files (350 MB each), containing behavior and imaging data.
OS: Windows 7 or higher, macOS X.
Jupyter Notebook, recommended installation: Anaconda, Python 2.7 or 3.6.
Installed Thunder libraries for image processing. For installing, run the following commands in shell (or Anaconda Prompt)
pip install https://github.com/thunder-project/thunder/zipball/master
pip install https://github.com/thunder-project/thunder-regression/zipball/master
pip install https://github.com/thunder-project/thunder-registration/zipball/master
The cluster needs to have distributed computing engine Spark running. Consult the official Spark documentation for details. See example on setting Spark on Janelia cluster.
Clone or download this repository. Download file 2014-08-01fish2_H2B/raw.zip separately (350 MB).
Start the Jupyter Notebook environment.
Open the notebook file FunctionalMaps_2014-08-01fish2(H2B).ipynb. Set the path to raw data downloaded and unzipped on your local computer:
expDir = `C:/../ZebrafishFunctionalMaps_LinearRegression-master/2014-08-01fish2_H2B/`
Execute the code cells in FunctionalMaps_2014-08-01fish2(H2B).ipynb, starting from top. By default, the code runs on your local computer.
If all blocks run successfully, functional maps of the fish brain will be saved in file ../proc/compositeRGBgamma0.5.tif after about 15 min. The TIFF red channel contains mapping for fictive swimming, green for forward stimulus, blue for backward stimulus. The file can be opened, for example, in Fiji.
Launch the Jupyter notebook environment on master node running a Spark cluster. Start the FunctionalMaps_2014-08-01fish2(H2B).ipynb notebook and change execution to distributed mode:
sparkOn = True
Then execute the code cells in sequential order, as before. The resulting functional maps will be saved in TIFF file.
2014-08-01fish2_H2B/raw.zip contains brain activity data from elavl3:GCaMP6-H2B (nuclear-localized GCaMP6f) fish during optomotor response behavior.
2016-07-26fish1_cyto/raw.zip contains brain activity data from elavl3:GCaMP6f (GCaMP6f expressed in the cytosol of neurons).
Each set contains 100 stacks (time points), downsampled to 1.62 micron/px (x,y) and 5 micron/px (z) spatial resolution. Temporal resolution is 0.55 s/stack.
If you use the code or data, please cite the original paper:
Brain-wide circuit interrogation at the cellular level guided by online analysis of neuronal function. Vladimirov et al, Nat. Methods, 2018.
To cite this code specifically, please use the following DOI