---
configs:
- config_name: worm_data_short
  data_files: 
  - split: train
    path: "worm_data_short.parquet"
language:
- en
license: mit
---

**CITATION**

[Q. Simeon, L. Venâncio, M. A. Skuhersky, A. Nayebi, E. S. Boyden and G. R. Yang, "Scaling Properties for Artificial Neural Network Models of a Small Nervous System," SoutheastCon 2024, Atlanta, GA, USA, 2024, pp. 516-524, doi: 10.1109/SoutheastCon52093.2024.10500049.](https://ieeexplore.ieee.org/document/10500049)

<a href="https://github.com/qsimeon/worm-data-preprocess">
  <img src="https://img.shields.io/badge/GitHub-100000?style=for-the-badge&logo=github&logoColor=white" />
</a>

**DATASET PROCESSING**

worm_data_short.parquet is generated by aggregating the info from 12 neural activity source datasets. 
Each source dataset is processed as follows:
1. **Loading** raw data in various formats (MATLAB files, JSON files, etc.).
1. Extracting relevant data fields (neuron IDs, traces, time vectors, etc.).
1. Cleaning data
1. **Resampling** the data to a common time resolution. - if requested
1. **Smoothing** the data using different methods - if requested
1. **Normalizing** data
1. Creating dictionaries to map neuron indices to neuron IDs and vice versa.
1. Saving the preprocessed data into a standardized format.

**DATASET CONFIG**

This dataset was preprocessed with the following hyperparameters. To modify or reproduce the dataset with new settings, refer to the [source code](https://github.com/qsimeon/worm-data-preprocess).

- `resample_dt`: `0.333` — Time step for resampling  
- `interpolate`: `"linear"` — Method used to fill missing data  
- `smooth`:  
  - `method`: `"moving"` — Smoothing algorithm (`none`, `gaussian`, `exponential`, `moving`)  
  - `alpha`: `0.5` — Exponential smoothing factor  
  - `sigma`: `5` — Gaussian kernel width  
  - `window_size`: `15` — Window size for moving average  
- `norm_transform`: `"standard"` — Type of normalization (`standard` or `causal`)


**FIGURE**

Compiled neural activity dataset from GCaMP calcium imaging of _C. elegans_ from multiple experimental sources, standardized to a common sampling rate and organization format.
![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/65cab82843207e438a9e7651/azsU9LuAl5N54FCTAK990.jpeg)

**EXAMPLE USAGE**

To use this dataset, you may load or download it using the [`datasets`](https://huggingface.co/docs/datasets/en/loading) and [`huggingface_hub`](https://huggingface.co/docs/huggingface_hub/en/guides/download) libraries, respectively.

See this notebook on an example of how to download the dataset and begin working with the data.
<a target="_blank" href="https://colab.research.google.com/drive/1z7h2gGuWhupRtjpYc7IHFD4rJ4kIsyuD#scrollTo=ZiZXMRc931oy">
  <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>

Google Colab notebook example of loading this dataset and then plotting a few samples of calcium data.
![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/65cab82843207e438a9e7651/FuzBcRZy6BQSsjOUjae47.jpeg)

**ORIGINAL DATA FILES**

We provide a [Dropbox link](https://www.dropbox.com/scl/fi/vfygz1twi1jg62cfssc0w/opensource_data.zip?rlkey=qa4vpwcoza3k9v5o2watwblth&dl=0) to download the original data that we obtained from various sources, including publicly available and unpublished data shared with us by researchers. The `raw_data_file` in the dataset table references these files.

If you'd like to preprocess the data from scratch using different preprocessing settings or datasets, you may do so using the code in the [worm-data-preprocess](https://github.com/qsimeon/worm-data-preprocess) repo.