Published June 17, 2024
| Version v1
Dataset
Open
1p_BLA_sync_permutation_social_valence
Description
Genetically- and spatially-defined basolateral amygdala neurons control food consumption and social interaction
Highlights:
- Classification of molecularly-defined glutamatergic neuron types in mouse BLA with distinct spatial expression patterns.
- BLALypd1 neurons are positive-valence neurons innately responding to food and promoting normal feeding.
- BLAEtv1 neurons innately respond to aversive and social stimuli.
- BLAEtv1 neurons promote fear learning and social interactions.
- Either using our demo files or your calcium imaging and behavior CSV files need to be used: Demo lists: 1. Figure4_food, 2. Figure5_social, 3. Figure5_fear_conditioning, 4. suppl.fig10_longitudinal_footshock_social.
Note
Demo files are already preprocessed H5 files, so you can skip 2-3steps.
- you need to download "core_codes" (logger.py, preprocessing.py, util.py) to synchronize the extracted behavior statistics with calcium traces (The TTL emission-reception delay is negligible (less than 30ms), therefore the behavioral statistics time series can be synchronized with calcium traces by the emission/receival time on both devices) and it would generate combined one H5 file (behavior+calcium data)
- Run Synchrnoize_h5generation.py code to apply core-codes (preprocessing) to your data:
import core.preprocessing as prep
- You can run each code (5 codes) described in the paper to generate the results: 1. Fear Conditioning, 2.social, 3. food, 4. permutation, 5, suppl.10 social_footshock.py code number 4 is the percentage comparison with shuffling of data in Figure4-5 as bar graph you can reproduce using the code: Figure4_5_permutation_bargraph.
Note
-System requirements Python (3.10.8): we used a Python IDE for professional developers by JetBrains, Pycharm. Packages: suite2p : https://github.com/MouseLand/suite2p
pip install git+https://github.com/MouseLand/suite2p.git
matplotlib
pip install matplotlib
pip install PyQt5
numpy
Warning
our code included : matplotlib Qt5Agg An Error is happening because Google Colab and Jupyter run on virtual environments which do not support GUI outputs as you cannot open new windows through a browser. Running it locally on a code editor(Spyder, or even IDLE) ensures that it can open a new window for the GUI to initialize.
Tip
- "our analysis pipeline is based on basic python packages:"
> import numpy as np
>import h5py as h5
>import pandas as pd
Installation guide above
- Demo -Demo_data.zip
Yue Zhang
https://github.com/limserenahansol/1p_BLA_sync_permutation_social_valence
Files
demo_Data.zip
Files
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