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| license: cc
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| # Spike waveform shards (derived from IBL dandiset 000409) |
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| A curated collection of per-spike multichannel waveform windows extracted from NWB assets in the DANDI dandiset 000409 (International Brain Laboratory, IBL). This repository contains the extractor and uploader used to produce Parquet shards; this README documents the derived dataset, its provenance, format, and how to reproduce it. |
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| ## Short description |
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| Parquet shards of spike waveform windows (channels × timesteps). Each row contains a fixed-shape multichannel waveform centered on a spike and related metadata (recording URI, unit identifier, spike time, channel indices, and extraction metadata). The dataset is intended for ML and analysis workflows operating on per-spike waveforms. |
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| ## Source / provenance |
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| - Primary source: DANDI Archive, Dandiset 000409 (International Brain Laboratory). See: https://dandiarchive.org/dandiset/000409 |
| - The list of candidate NWB asset URIs used during extraction is stored here: [feature_extractor/dandi_downloader/dandi_list.txt](feature_extractor/dandi_downloader/dandi_list.txt) |
| - Note: not every URI in that list was necessarily processed — the Hugging Face dataset contains the subset of assets that were successfully downloaded and extracted. |
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| Original dandiset summary (selected fields): |
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| - Title: IBL - Brain Wide Map [deprecated] |
| - ID: 000409 |
| - License: spdx:CC-BY-4.0 (verify per-asset license/metadata) |
| - Related resource: https://doi.org/10.1101/2023.07.04.547681 |
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| Refer to the original DANDI page for the full contributor list, asset-level metadata, and licensing details. |
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| ## What the dataset contains |
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| - File type: Parquet (.parquet) shards (row-wise shards; default shard_rows=10000 in the extractor). |
| - Typical per-row fields (inspect shards to confirm exact schema): |
| - `recording_uri` — original NWB/DANDI URI |
| - `unit_id` — identifier for the unit within the NWB |
| - `spike_time` — spike time in seconds |
| - `waveform` — array/tensor (channels × timesteps) |
| - `peak_channel` / `channel_indices` — channels included in the window |
| - extraction metadata: sampling rate, sample index, extractor params (when present) |
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| Notes: |
| - The extractor performs minimal filtering by default (no normalization, no SNR filtering) unless explicitly configured. |
| - Check a sample shard with `pyarrow` or `pandas` to confirm exact field names and dtypes. |
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| ## How the dataset was produced |
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| - Workflow overview: |
| 1. Download NWB asset (via `dandi` CLI, S3, or direct HTTP after resolving dandi:// URIs). |
| 2. Open NWB/HDF5, locate `ElectricalSeries` and unit spike times/metadata. |
| 3. For each spike, compute corresponding sample index (or use timestamps) and extract a fixed-size waveform window centered on the spike at the unit's peak channel. |
| 4. Pad/truncate windows at edges to ensure a fixed `(channels, timesteps)` shape. |
| 5. Aggregate rows and write Parquet shards. |
| 6. Optionally upload shards using the uploader helper. |
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| ## Typical extraction parameters (defaults) |
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| - `channels`: 25 |
| - `timesteps`: 300 |
| - `shard_rows`: 10000 |
| - `compression`: zstd |
| - `max_spikes_per_unit`: 500 |
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| Actual dataset shards may have been produced with different parameter overrides; inspect the shard metadata or the extractor run logs for precise parameters used. |
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| ## Data licensing and attribution |
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| - This dataset is a derived product of NWB assets hosted on DANDI. Users must comply with the license and attribution requirements of the original assets. The dandiset lists `spdx:CC-BY-4.0`, but please verify per-asset metadata on DANDI for any variations. |
| - When using or publishing results based on these shards, cite the original DANDI dandiset and the related IBL publication. |
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| ## Citation |
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| Please cite: |
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| - International Brain Laboratory — DANDI Dandiset 000409. https://dandiarchive.org/dandiset/000409 |
| - A Brain-Wide Map of Neural Activity during Complex Behaviour (preprint): https://doi.org/10.1101/2023.07.04.547681 |
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| If you use the Hugging Face dataset derived from these shards, also cite the HF dataset page (include the HF dataset identifier and URL) |
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| ## Inspecting shards / example |
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| Load a shard with pandas / pyarrow: |
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| ```python |
| import pyarrow.parquet as pq |
| import pandas as pd |
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| tbl = pq.read_table('/path/to/shard_00000.parquet') |
| df = tbl.to_pandas() |
| print(df.columns) |
| print(df.iloc[0]) |
| ``` |
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| Last updated: 2026-02-02 |
