Add example notebook for 001757 (Embargoed)

001757/IBL-Mesoscope/public_demo/README.md

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+# IBL - Mesoscopic Imaging Data
+
+This example notebook demonstrates how to access the dataset published at [DANDI:001757](https://dandiarchive.org/dandiset/001757/draft).
+
+This project aims to generate a rich, large-scale dataset capturing the activity of defined neural populations during the IBL decision-making task, using a 2-photon random access mesoscope. By imaging calcium activity in excitatory neurons across the dorsal cortex of transgenic mice, we seek to characterize how population-level neural activity encodes key task variables such as stimulus, choice, and bias context. Imaging functionally connected regions simultaneously allows us to investigate interregional interactions and trial-to-trial dynamics, while repeated recordings across days will help assess the stability of these neural representations over time and their relationship to expert performance.
+
+## Installing the dependencies
+
+```bash
+git clone https://github.com/dandi/example-notebooks
+cd example-notebooks/001757/IBL-Mesoscope
+conda env create --file environment.yml
+conda activate 001757_demo
+```

001757/IBL-Mesoscope/public_demo/environment.yml

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+name: 001757_demo
+channels:
+    - conda-forge
+dependencies:
+    - python==3.13
+    - ipywidgets
+    - pip
+    - pip:
+          - dandi
+          - jupyter
+          - matplotlib
+          - pynwb
+          - remfile
+          - plotly
+          - ndx_anatomical_localization

001757/IBL-Mesoscope/public_demo/load_nwb_utils.py

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+# Core data manipulation and analysis
+from pathlib import Path
+
+# NWB access
+import h5py
+
+# DANDI access
+import remfile
+from dandi.dandiapi import DandiAPIClient
+from pynwb import NWBHDF5IO
+
+
+def load_nwb_from_dandi(dandiset_id, subject_id, session_id, description):
+    """
+    Load NWB file from DANDI Archive via streaming.
+    """
+    pattern = f"sub-{subject_id}/sub-{subject_id}_ses-{session_id}_desc-{description}*.nwb"
+
+    with DandiAPIClient() as client:
+        client.dandi_authenticate()
+        assets = client.get_dandiset(dandiset_id, "draft").get_assets_by_glob(pattern=pattern, order="path")
+
+        s3_urls = []
+        for asset in assets:
+            s3_url = asset.get_content_url(follow_redirects=1, strip_query=False)
+            s3_urls.append(s3_url)
+
+        if len(s3_urls) != 1:
+            raise ValueError(f"Expected 1 file, found {len(s3_urls)} for pattern {pattern}")
+
+        s3_url = s3_urls[0]
+
+    file = remfile.File(s3_url)
+    h5_file = h5py.File(file, "r")
+    io = NWBHDF5IO(file=h5_file, load_namespaces=True)
+    nwbfile = io.read()
+
+    return nwbfile, io
+
+
+def load_nwb_local(directory_path, subject_id, session_id, description):
+    """
+    Load NWB file from local directory.
+    """
+    directory_path = Path(directory_path)
+    pattern = f"sub-{subject_id}/sub-{subject_id}_ses-{session_id}_desc-{description}*.nwb"
+    matches = list(directory_path.glob(pattern))
+    if len(matches) != 1:
+        raise ValueError(f"Expected 1 file, found {len(matches)} for pattern {pattern}")
+    nwbfile_path = matches[0]
+
+    io = NWBHDF5IO(path=nwbfile_path, load_namespaces=True)
+    nwbfile = io.read()
+
+    return nwbfile, io