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Released NWB: Neurophysiology 2.0 Datasets

These sample data sets have been translated into the Neurodata Without Borders: Neurophysiology unified data format, which has been developed to incorporate present and future electrophysiological and optical physiology data and to include complex metadata related to stimuli and behavior. To learn more about the data sets, visit the links below.  This is not a comprehensive list and is provided as a convenience. Many of the datasets and tools are built and supported by other groups, and are in active development.

Allen Institute for Brain Science: pre-release

A collection of pre-release example datasets is available for download including passive viewing extracellular electrophysiology, visual behavior calcium imaging, and intracellular in-vitro electrophysiology.

DOWNLOAD.

Intracellular Electrophysiology
Intracellular in-vitro electrophysiology
Passive viewing extracellular electrophysiology
Visual behavior calcium imaging

Allen Institute for Brain Science: Visual Coding Neuropixels Data

The Allen Institute for Brain Science has released its first — and the world’s largest — dataset of electrical brain activity gathered using Neuropixels, a new high-resolution silicon probe that can read out activity from hundreds of neurons simultaneously. This initial data release consists of 58 experiments. Each experiment contains data from up to six Neuropixels probes recording in cortex, hippocampus, and thalamus. Data for each experiment is conveniently packaged in Neurodata Without Borders (NWB) files that can be downloaded via the Allen SDK. For further details see the news release by the Allen Institute as well as the Visual Coding – Neuropixels website.

Frank Lab, UCSF, hippocampus electrophysiology recordings during spatial navigation

The data was recorded from hippocampus regions CA1 and CA3 (or MEC and CA1) from nine male Long-Evans rats before, during and after the animals performed an alternate choice task in one of two W-shaped tracks.  The data was used to determine relationships between activity in hippocampus neurons to information representation, learning and decision making.

DOWNLOAD. Convert to NWB (Jupyter notebook). Query and analysis and comparison with Allen Institute Data.

Buzsáki Lab, NYU, hippocampus electrophysiology recordings during spatial navigation

Electrophysiology recordings from hippocampal regions of mice in theta-maze and in open exploration, from Senzai, Yuta, and György Buzsáki. “Physiological properties and behavioral correlates of hippocampal granule cells and mossy cells.” Neuron.

DOWNLOAD.

Anne Churchland Lab, Cold Spring Harbor Laboratory, calcium imaging during decision making

Calcium imaging dataset accompanying the paper:

Farzaneh Najafi, Gamaleldin F Elsayed, Robin Cao, Eftychios Pnevmatikakis, Peter E Latham, John Cunningham, Anne K Churchland. “Excitatory and inhibitory subnetworks are equally selective during decision-making and emerge simultaneously during learning” bioRxiv (2018): 354340.

DOWNLOAD. python demo. MATLAB demo.

Svoboda Lab (Janelia Research Campus)

An ongoing DataJoint-NWB interoperability project showcasing data with DataJoint pipeline and exported NWB 2.0 files. This project involves data from 11 published studies from the Svoboda Lab  at the Janelia Research Campus.

Demo

PyNWB Test Data

PyNWB generates as part of its test suite a collection of small NWB files with synthetic test data.

DOWNLOAD.

Allen Cell Types Database

There are 86 billion neurons in the adult human brain, and like snowflakes, no two are exactly the same. Brain cells are found in a dizzying array of intricate shapes, have different electrical patterns and functions, and express different genes. Sorting these cells into “types” is an enormous and complex challenge, but before we can hope to understand our brains, we need to create a rich list of its building blocks.

The Allen Cell Types Database is a new tool to help scientists create that list, and to understand what makes one type of cell different from another.  “Identifying neuronal cell types is essential to unraveling the mystery of how the brain processes information and gives rise to perception, memory and consciousness,” says Christof Koch, President and Chief Scientific Officer of the Allen Institute for Brain Science. “This is the first resource of its kind to bring together multiple types of data—shape, position in the brain and electrical activity—in a single searchable database anywhere on the planet.”

Data in the Allen Cell Types Database is organized in an alpha version of the NWB format and will be updated in later releases.

Overview of the Allen Human Brain Atlas

Cell Feature Filters

cell-feature-filters

Electrophysiology Data Summary

Electrophysiology Summary

NWB:N 1.0 Datasets

NWB:N data sets have been published in the newer NWB 2.0 standard and the older NWB 1.0 version.

For an updated list of NWB:N 2.0 data sets, see here: https://neurodatawithoutborders.github.io/exampledata. These data sets can be read by the latest versions of PyNWB and MatNWB.

The majority of NWB:N 1.0 data sets are hosted at CRCNS.org. CRCNS (Collaborative Research in Computational Neuroscience) is a joint program of NSF and NIH that supports integration of theoretical and experimental neuroscience through collaborative research projects.

The following data sets represent the primary use cases for the development of the NWB format:

  • Rat hippocampus, contributed by György Buzsáki, New York University (CRCNS hc-3 data set)
  • Mouse slice electrophysiology, contributed by the Allen Institute (CRCNS pvc-6 data set)
  • Electrophysiological recordings from rat barrel cortex, contributed by Karel Svoboda, Janelia Research Campus (HHMI) (CRCNS alm-1  data set)
  • Calcium imaging of rat somatosensory cortex, contributed by Karel Svoboda, Janelia Research Campus (HHMI) (CRCNS ssc-1 data set)
  • Retina, contributed by Markus Meister at the California Institute of Technology (CRCNS ret-1 data set)

This list is no longer kept updated. New users of NWB:N are recommended to use datasets published in NWB 2.0 (see above) as a reference.

Disclaimer:

Reference herein to any specific data, product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not constitute or imply its endorsement, recommendation, or favoring by the NWB team, United States Government or any agency thereof, The Regents of the University of California, or the Kavli foundation. Use of the Neurodata Without Borders name for endorsements is prohibited.

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