A core goal of neuroscience is to discover temporal patterns in + behavior and neurophysiology. Though a variety of tools exist to + characterize these relationships, there is still no substitute for + direct inspection as a way to notice unexpected patterns and generate + new hypotheses. To facilitate this process, we have developed the + Systems Neuro Browser (SNUB), a graphical user interface for exploring + time-series data. SNUB is a flexible, general-purpose tool that allows + users to build a dashboard of synchronized data views, including + neural recordings, behavioral videos, and annotations derived from + these data.
+Direct inspection of behavior and neurophysiology recordings is + hard because the data are typically high-dimensional and come in a + variety of modalities (such as raw video, pose tracking, spike trains, + calcium traces, etc.) with different sampling rates and methods of + visualization. SNUB lowers the activation energy for data exploration + by integrating these data streams into a single easy-to-navigate + interface. The main intended user is a researcher who has collected + data and started to analyze it (e.g. in Python). They may already be + generating static versions of the visualizations afforded by SNUB, + such as aligned heatmaps and trace plots, and now would like a + frictionless way to pan/zoom around these plots and keep all the data + views linked together. Importantly, SNUB should be thought of as akin + to a plotting library, rather than a data analysis tool.
+The interface is divided into synchronized windows that each show a
+ different data stream. The linked data views allow users to quickly
+ inspect the relationships between experimental phenomena, such as the
+ behaviors that occur during a particular pattern of neural activity
+ (
Screenshot from
+ SNUB.
We provide dedicated widgets and loading functions for exploring + raw video, 3D animal pose, behavior annotations, electrophysiology + recordings, and calcium imaging data—either as a raster or as a + super-position of labeled regions of interest (ROIs). More broadly, + SNUB can display any data that takes the form of a heatmap, scatter + plot, video, or collection of named temporally-varying signals.
+In addition to the front-end GUI, we include a library of functions + that ingest data (or paths to the data) and visualization parameters, + and then organize these in a format that is quickly readable by the + SNUB viewer. The following code, for example, creates a project with + paired electrophysiology and video data.
+snub.io.create_project(project_directory, duration=1800)
+snub.io.add_video(project_directory, 'path/to/my_video.avi', name='IR_camera')
+snub.io.add_spikeplot(project_directory, 'my_ephys_data', spike_data)
+ We also provide a rudimentary tool for automatically generating
+ SNUB datasets from Neurodata Without Borders (NWB) files, which
+ contain raw and processed data from neuroscience recordings
+ (
SNUB is a flexible general-purpose tool that complements more
+ specialized packages such as rastermap
+ (
The graphics in SNUB are powered by vispy
+ (
The SNUB documentation includes a set of tutorials that make use of
+ original data collected in the Datta lab between 2020 and 2022. All
+ experimental procedures were approved by the Harvard Medical School
+ Institutional Animal Care and Use Committee (Protocol Number 04930)
+ and were performed in compliance with the ethical regulations of
+ Harvard University as well as the Guide for Animal Care and Use of
+ Laboratory Animals. Experimental protocols and processed data have
+ been deposited on Zenodo
+ (
CW is a Fellow of The Jane Coffin Childs Memorial Fund for Medical
+ Research. SRD is supported by NIH grants U19NS113201, RF1AG073625,
+ R01NS114020, the Brain Research Foundation, and the Simons
+ Collaboration on the Global Brain. The SNUB app icon was adapted from
+ a drawing contributed to scidraw by Luigi Petrucco
+ (