Optic_flow_RF_estimation_Zhang_et_al_2022/README.md

Data & code for Zhang, Huang, Nörenberg & Arrenberg 2022

This repository contains data and code for our 2022 manuscript "A robust receptive field code for optic flow detection and decomposition during self-motion" by Zhang, Huang, Nörenberg & Arrenberg. The corresponding author is Aristides B. Arrenberg.

Prerequisites:

Code was developed and tested in MATLAB version 2021b. The content of this package can be placed anywhere on your MATLAB path.

Please add all files in the data and bin folders to the Matlab search path before running any scripts by:

1. Go to the Home tab → click Set Path
2. Click Add with Subfolders and select the data and bin folder
3. Click save and close.

The "code" folder:

This folder contains the Matlab functions/classes used in the Matlab scripts in the figure scripts folder.

• imread_big.m: An open-source matlab function for loading large multipage TIFF file, published by user "Tristan Ursell" on MATLAB Central.

The "data" and "figure script" folders:

The data and figure script folders contains the required processed data and the Matlab live scripts (.mlx) respectively for reproducing figures and supplementary figures in the manuscript. The plotting scripts load the processed data by their hard-coded relative path.

The subfolder raw Ca Data in the data folder contains an example raw calcium imaging TIFF file and the corresponding text file for stimulus-recording timeline synchronization for the demonstration file for calcium preprocessing, ca_prep_demo.mlx .

License:

Data

• Upon publication of the manuscript in a peer-reviewed journal, all files in the data folder will be published under Creative Commons license CC BY-NC-SA 4.0 (see the LICENSE file in the data folder).

Software

• All files in the code and figure scripts folder will be published under Creative MIT license (see the LICENSE file in the code folder).