2019 Smartcages Study

Overview

This repository contains code and analysis scripts for the study "Intensive longitudinal characterization of multidimensional biobehavioral dynamics in laboratory rats," published in Cell Reports (Hasanpour et al., 2021, DOI: 10.1016/j.celrep.2021.108987). The study examines the basal biobehavioral dynamics of group-housed laboratory rats (Lister Hooded, Long-Evans, Sprague-Dawley, and Wistar strains) from postnatal day 22 to 97, using wireless tracking and videography.

Study Highlights

• Sex and Strain Differences: Identifies sex- and strain-dependent bi-stable developmental states in rat behavior from adolescence to adulthood.
• Circatidal-like Rhythms: Detects ~12.4-hour locomotor activity rhythms, resembling circatidal patterns typically seen in coastal animals.
• Thigmotaxic Behavior: Suggests that movement along cage walls may reflect random walk patterns in constrained spaces, not stress.
• Data Scale: Analyzes over 130 billion data points from RFID tracking, HD video, and environmental sensors (temperature, humidity).

Repository Contents

• notebooks/: Jupyter Notebooks (94.2%) for data processing, statistical analysis, and visualization (e.g., locomotor activity, social interactions).
• matlab/: MATLAB scripts (4.4%) for spectral analysis (Fourier, wavelet, autocorrelation) and potential landscape modeling.
• data/: Placeholder for raw/processed datasets (not included due to size; contact authors for access).
• other/: Miscellaneous files (1.4%) for preprocessing or configuration.

Key Analyses

• Linear Mixed Effects (LME) Models: Assesses effects of strain, sex, and age on behavior and physiology.
• Potential Landscape Analysis: Models bi-stable states using the Langevin equation.
• Spectral Analysis: Identifies circadian (~24-hour) and circatidal-like (~12.4-hour) rhythms.
• Random Walk Simulations: Compares rat movement to random walk models to explain thigmotaxis.

Requirements

• Python: Jupyter Notebook with:
  • numpy, pandas, scipy (data processing)
  • matplotlib, seaborn (visualization)
  • statsmodels (statistical modeling)
• MATLAB: For running spectral and potential landscape analyses.
• Data: Raw datasets available via the study's data repository or by contacting the authors.

Usage

1. Clone the Repository:

   git clone https://github.com/afreeentity/2019_smartcages_study.git
   cd 2019_smartcages_study
   

Install Dependencies:

Python: pip install -r requirements.txt Ensure MATLAB is installed for .m scripts.

Run Analyses:

Open notebooks/ in Jupyter for data exploration (e.g., locomotor_analysis.ipynb). Run MATLAB scripts in matlab/ for advanced analyses like wavelet spectrograms.

License Licensed under the MIT License. Citation Please cite the original paper if using this code or data:

Hasanpour, M., Mitricheva, E., Logothetis, N., & Noori, H. R. (2021). Intensive longitudinal characterization of multidimensional biobehavioral dynamics in laboratory rats. Cell Reports, 35(2), 108987. DOI: 10.1016/j.celrep.2021.108987