Neurodata Without Borders

We provide a rudimentary tool for automatically generating a SNUB project from NWB files, which contain raw and processed data from neuroscience recordings. The data are stored hierarchically, and each component of the hierarchy has a specific neurodata type that reflects the measurement modality (e.g Units for spike trains, ImageSeries for video, etc.). Our conversion tool generates a SNUB subplot for each supported neurodata type. Users can optionally restrict this process to a subset of the NWB hierarchy (e.g. include pose tracking while excluding electrophysiology, or include just a subset of electrophysiology measurements).

Neurodata types

The following neurodata types are supported:

  • IntervalSeries

    Contains start and end times for (possibly labeled) intervals. A SNUB trace plot is generated containing one trace per interval type.

  • RoiResponseSeries

    Contains fluorescence traces for regions of interest (ROIs). A SNUB heatmap is generated containing one row per ROI. Metadata associated with each ROI is not linked in the SNUB plot.

  • TimeSeries

    Contains time series in one or more dimensions. A SNUB heatmap is generated for 15 or more dimensions, and a SNUB trace plot is generaed for fewer than 15 dimensions.

  • PoseEstimation

    Contains pose tracking data (available via the ndx-pose extension). A SNUB trace plot is generated for each tracked body part and spatial dimension. For 3D data, a 3D pose plot is also generated.

  • ImageSeries

    Contains video data. We assume that the video is stored as a separate file and that the ImageSeries object contains frame timestamps and a relative path to that file. A SNUB video plot is then generated.

  • LabelSeries

    Contains discrete label time series in the form of a binary matrix with one column per label abd one row per time bin (available via the ndx-labels extension). A SNUB heatmap is generated directly from this matrix.

  • TimeIntervals

    Contains annotated intervals. Each interval has a start time, a stop time, and an arbitrary number of additional metadata fields. A SNUB trace plot is generated with one trace showing the start and stop times of each interval. All other metadata is ignored since it cannot be canonically represented using the currently available SNUB plot types.

  • Position

    Contains position data in the form of one or more SpatialSeries objects. A SNUB trace plot is generated with traces for each spatial dimensions of each consistuent spatial series.

  • SpatialSeries

    Contains spatial data in the form of a time series with one or more dimensions. A standalone SNUB trace plot is generated for the spatial series if it is not contained within a Position object.

  • Units

    Contains spike trains for one or more units. A corresponding SNUB spike plot is generated.

  • Events

    Contains a sequence of unlabeled event times (available via the ndx-events extension). A SNUB trace plot is generated with a single trace that spikes at each event time.

Examples

For each example, run the first code block in a terminal and the second in a python console or notebook.

A change in behavioral state switches the pattern of motor output that underlies rhythmic head and orofacial movements

Liao, Song-Mao; Kleinfeld, David; Rinehart, Duane; University of California San Diego (2023) Dataset for: A change in behavioral state switches the pattern of motor output that underlies rhythmic head and orofacial movements (Version 0.230515.0530) [Data set]. DANDI archive. https://doi.org/10.48324/dandi.000540/0.230515.0530

Includes the following SNUB-compatible neurodata types: TimeSeries, ImageSeries

# Download NWB file
dandi download https://api.dandiarchive.org/api/dandisets/000540/versions/0.230515.0530/assets/94307bee-459c-424e-b3a0-1e86b23f04b2/download/

# Download associated video and create directory for it
dandi download https://api.dandiarchive.org/api/dandisets/000540/versions/0.230515.0530/assets/942b0806-2c8b-4289-a072-9e965884fcb6/download/
mkdir sub-SLR087_ses-20180706_obj-14ua2bs_behavior+image
mv 9557b48e-46f0-45f2-a700-a2e15318c5bc_external_file_0.avi sub-SLR087_ses-20180706_obj-14ua2bs_behavior+image/

import os, snub

# Define paths
nwb_file = "sub-SLR087_ses-20180706_obj-14ua2bs_behavior+image.nwb"
name = os.path.splitext(os.path.basename(nwb_file))[0]
project_directory = os.path.join(os.path.dirname(nwb_file), f"SNUB-{name}")

# Make SNUB plot that includes video and torso tracking
snub.io.create_project_from_nwb(project_directory, nwb_file, branches=['torso_dlc', 'ImageSeries'])

A Unified Framework for Dopamine Signals across Timescales

Kim, HyungGoo; Malik, Athar; Mikhael, John; Bech, Pol; Tsutsui-Kimura, Iku; Sun, Fangmiao; Zhang, Yajun; Li, Yulong; Watabe-Uchida, Mitsuko; Gershman, Samuel; Uchida, Naoshige (2023) A Unified Framework for Dopamine Signals across Timescales (Version draft) [Data set]. DANDI archive. https://dandiarchive.org/dandiset/000251/draft

Includes the following SNUB-compatible neurodata types: TimeSeries, TimeIntervals, SpatialSeries, Events

# Download NWB file
dandi download https://api.dandiarchive.org/api/dandisets/000251/versions/draft/assets/b28fcb84-2e23-472c-913c-383151bc58ef/download/

import os, snub

# Define paths
nwb_file = "sub-108_ses-Ca-VS-VR-2.nwb"
name = os.path.splitext(os.path.basename(nwb_file))[0]
project_directory = os.path.join(os.path.dirname(nwb_file), f"SNUB-{name}")

# Make SNUB plot
snub.io.create_project_from_nwb(project_directory, nwb_file)

Neural population dynamics during reaching

Churchland, Mark; Cunningham, John P.; Kaufman, Matthew T.; Foster, Justin D.; Nuyujukian, Paul; Ryu, Stephen I.; Shenoy, Krishna V. (2022) Neural population dynamics during reaching (Version draft) [Data set]. DANDI archive. https://dandiarchive.org/dandiset/000070/draft

Includes the following SNUB-compatible neurodata types: Units, TimeIntervals, Position

# Download NWB file
dandi download https://api.dandiarchive.org/api/dandisets/000070/versions/draft/assets/7b95fe3a-c859-4406-b80d-e50bad775d01/download/

import os, snub

# Define paths
nwb_file = "sub-Jenkins_ses-20090912_behavior+ecephys.nwb"
name = os.path.splitext(os.path.basename(nwb_file))[0]
project_directory = os.path.join(os.path.dirname(nwb_file), f"SNUB-{name}")

# Make SNUB plot
snub.io.create_project_from_nwb(project_directory, nwb_file)