Analysis of hippocampal ensembles during Contextual Feeding and cNOR tasks
Gava GP
Lefevre L
Description
This dataset contains two jupyter notebooks and python scripts to run some exemplar analysis from the article 'Organising the coactivity structure of the hippocampus from robust to flexible memory'.
The jupyter notebooks provided are:
- 'cNOR_task.ipynb' which computes the object/location coding analyses shown in Figures 1 and 4
- 'coactivity_cond+cnor.ipynb' reproduces some of the coactivity analyses shown in Figures 1 and 4.
In the 'results' folder are stored processed data that are loaded throughout the notebooks.
The python script 'makeGraphbatch.py' computes coactivity graphs during active exploration times (theta-informed) from the spiking data. After downloading, ensure the spiking data folder is named 'data' and placed inside the root folder 'orgCoactHippo'. See script for more info.
Inside the 'recordings' folder, there are text files that list the recording days belonging to each task. That is: 'cond_ll145' and 'cond_ll149' lists the food-context conditioning days for each animal, while `cnor_x` and `cnor_y` list the cnor days in the two contexts, regardless of the animal's identity.
The python library 'util_func.py' data loading and processing functions used by the python script and notebooks. See script for more info.
'difference_estimation_plot.py' is a python library to produce estimation plots as in the article.
For the analysis in the original paper, this code was run in Python version 3.10. Execution of the code requires the following libraries:
matplotlib 3.7.1
matplotlib-inline 0.1.6
networkx 2.8.4
numpy 1.24.3
pandas 1.5.3
pandas-ods-reader 0.1.4
scikit-learn 1.2.2
scipy 1.10.1
seaborn 0.12.2
Assistance with this dataset
We welcome researchers wishing to reuse our data to contact the creators of datasets. If you are unfamiliar with analysing the type of data we are sharing, have questions about the acquisition methodology, need additional help understanding a file format, or are interested in collaborating with us, please get in touch via email. Our current members have email addresses on our main site. The corresponding author of an associated publication, or the first or last creator of the dataset are likely to be able to assist, but in case of uncertainty on who to contact, email Ben Micklem, Research Support Manager at the MRC BNDU.
Year Published
2024
DOI
10.60964/bndu-r97n-bg26
Funders & Grant Numbers
BBSRC, UKRI (BB/S007741/1, 376 BB/N002547/1)
MRC, UKRI (MC_UU_00003/4, MR/W004860/1)
Publisher
University of Oxford
Downloaded times
First Published In
2024. Science, 385(6713):1120-1127.
Free Full Text PDF here
Group
Terms
Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
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