| # CANNS Analysis Datasets |
|
|
| This repository contains example datasets for the [CANNS (Continuous Attractor Neural Networks)](https://github.com/your-username/canns) data analysis package. |
|
|
| ## Datasets |
|
|
| ### ROI_data.txt (703 KB) |
| - **Description**: 1D CANN ROI data for bump analysis |
| - **Format**: Text file with neural activity measurements |
| - **Usage**: 1D CANN analysis, MCMC bump fitting |
| - **Example**: Used in 1D CANN analysis tutorials |
| |
| ### grid_1.npz (8.7 MB) |
| - **Description**: Grid cell spike data with position information |
| - **Format**: NumPy archive containing spike times, positions |
| - **Keys**: `spike` (spike times), `t` (time), `x`, `y` (positions) |
| - **Usage**: 2D CANN analysis, topological data analysis, circular coordinate decoding |
| - **Example**: Primary dataset for 2D CANN tutorials |
|
|
| ### grid_2.npz (4.5 MB) |
| - **Description**: Second grid cell dataset for comparison studies |
| - **Format**: NumPy archive with spike and position data |
| - **Usage**: Comparative analysis, validation studies |
| |
| ### Left_Right_data_of(604 MB) |
| pretty_name: "ASA-format MEC grid-cell dataset (Open Field only)" |
| tags: |
| - neuroscience |
| - grid-cells |
| - MEC |
| - open-field |
| - continuous-attractor-neural-network |
| - topological-data-analysis |
| - ASA-format |
| |
| # Dataset Summary |
| This dataset contains **ASA-format** conversions of MEC recordings restricted to **Open Field (OF)** sessions only. |
| Each session is provided as a NumPy `.npz` file (full session + optional module subsets) with a lightweight JSON manifest for indexing. |
| |
| # Original Source |
| - **EBRAINS dataset instance**: https://search.kg.ebrains.eu/instances/4080b78d-edc5-4ae4-8144-7f6de79930ea |
| |
| ## Files Overview |
| |
| ### *_ASA_mec_full_cm.npz |
| - **Description**: ASA-format Open Field (OF) MEC session data (all units included) |
| - **Format**: NumPy archive (`.npz`) following the ASA schema |
| - **Keys**: `spike` (neural spikes/activity), `t` (time), `x`, `y` (positions), `meta` (session metadata) |
| - **Usage**: Full-session analysis with ASA (CANN / TDA / decoding), baseline for module comparisons |
| - **Example**: Primary input file to run end-to-end OF analysis in the ASA pipeline |
| |
| ### *_ASA_mec_gridModuleXX_nN_cm.npz |
| - **Description**: ASA-format subset files containing grid cells from a specific module (Module XX, n=N cells) for the same OF session |
| - **Format**: NumPy archive (`.npz`), same ASA schema as the full file, but restricted to one module’s grid cells |
| - **Keys**: `spike`, `t`, `x`, `y`, `meta` |
| - **Usage**: Faster experiments, module-wise topology/decoding analysis, comparing manifolds across modules |
| - **Example**: Run TDA on Module 01 vs Module 02 to compare torus quality and decoding stability |
|
|
| ### *_ASA_manifest.json |
| - **Description**: Per-session manifest summarizing the source `.mat`, generated ASA outputs, unit counts, and module splits |
| - **Format**: JSON metadata index |
| - **Usage**: Batch processing, programmatic iteration over sessions, auto-generating documentation without loading large `.npz` |
| - **Example**: Parse manifests to list all sessions and locate their corresponding full/module `.npz` files |
| |
| # Reference |
| Please refer to the EBRAINS instance above for the original dataset description and citation requirements. |
| |
| ## Usage |
| |
| Install the CANNS package and use the datasets module: |
| |
| ```python |
| from canns import datasets |
| from canns.analyzer import data_analysis |
| |
| # Automatic dataset download and setup |
| datasets.quick_setup() |
| |
| # Load specific datasets |
| roi_data = datasets.load_roi_data() |
| grid_data = datasets.load_grid_data("grid_1") |
| |
| # Use with analysis tools |
| analyzer = data_analysis.CANNDataAnalyzer() |
| spikes, x, y, t = analyzer.load_spike_data(datasets.get_dataset_path("grid_1")) |
| ``` |
| |
| ## Examples |
| |
| See the [CANNS examples](https://github.com/your-username/canns/tree/master/examples) for complete tutorials: |
| |
| - `data_analysis_demo.py`: Command-line demo |
| - `cann_data_analysis_tutorial.ipynb`: Jupyter notebook tutorial |
| |
| ## Citation |
| |
| These datasets are derived from the [CANN-data-analysis](https://github.com/Airs702/CANN-data-analysis) repository. Please cite: |
| |
| ```bibtex |
| @software{cann_data_analysis, |
| title = {CANN Data Analysis}, |
| url = {https://github.com/Airs702/CANN-data-analysis}, |
| author = {Airs702}, |
| year = {2024} |
| } |
| ``` |
| |
| ## License |
| |
| Please refer to the original [CANN-data-analysis repository](https://github.com/Airs702/CANN-data-analysis) for license information. |
| |
| --- |
| |
| *Generated automatically for the CANNS package datasets.* |
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