This is a repo for behavioral modeling for worm odor-navigation reported in the paper: https://arxiv.org/abs/2311.07117 (Chen et al. 2023). The repo analyzes behavioral trajectories that are output from the high-throughput worm tracking pipeline in the Leifer lab (https://github.com/Kevin-Sean-Chen/leifer-Behavior-Triggered-Averaging-Tracker-new) The corresponding data for figure making and analysis can be found in figshare: 10.6084/m9.figshare.24764403
Please download the data set from figure, adjust the corresponding downloaded directory, and run scripts in the figures folder.
Figures should be self-contained in this folder. To generate figures from the original data, please check the fig_note.txt document in figshare folder describes specific scripts and data to use for analysis from scratch.
To validate the generative model and inference procedure, we use code in the demo folder to simulate behavioral output given random odor concentration and infer ground-truth parameters.
Run mGLM.m for the dPAW model proposed in our paper. A simplified turning model is shown in bGLM.m.
We use scripts in inference folder and optimize objectives in the functions folder to fit models. Specifically, we use Chemotaxis_inference_pop.m and classify_learn3.m to fit MLE of parameters and to run cross-validation,
use mutant_fit.m to fit to different worm strains, and use opto_mGLM.m to fit to perturbation data.
To analyze tracks and pre-process data for model fitting, we use files in the scripts folder. Specifically, BRW_WV_CI.m is used to compute different chemotaxis indices,
OdorFlow_3.m is used to visualize behavioral trajectories given parameters. We call track2data.m functions in the function folder to save as Data structure that contains fields for analysis.
To load from raw data, please include https://github.com/Kevin-Sean-Chen/leifer-Behavior-Triggered-Averaging-Tracker-new repo to use additional functions.
If you use the design files and/or codes provided in this repository, please cite:
Kevin S. Chen, Jonathan W. Pillow, Andrew M. Leifer. (2023). Olfactory learning alters navigation strategies and behavioral variability in C. elegans arXiv:2311.07117
Design files and codes provided in this repository are free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 3 of the License, or (at your option) any later version.
This repository is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.