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Concepts

Acquisition Tools for Electrophysiology

Neuropixels Probes

Neuropixels probes were developed by a collaboration between HHMI Janelia, industry partners, and others1. Since their initial release in October 2018, 300 labs have ordered 1200 probes. Since the rollout of Neuropixels 2.0 in October 2020, IMEC has been shipping 100+ probes monthly (correspondence with Tim Harris).

Neuropixels probes offer 960 electrode sites along a 10mm long shank, with 384 recordable channels per probe that can record hundreds of units spanning multiple brain regions (Neuropixels 2.0 version is a 4-shank probe with 1280 electrode sites per shank). Such large recording capacity has offered tremendous opportunities for the field of neurophysiology research, yet this is accompanied by an equally great challenge in terms of data and computation management.

Data Acquisition Tools

Some commonly used acquisition tools and systems by the neuroscience research community include:

Data Preprocessing Tools

The preprocessing pipeline includes bandpass filtering for LFP extraction, bandpass filtering for spike sorting, spike sorting, manual curation of the spike sorting results, and calculation of quality control metrics. In trial-based experiments, the spike trains are aligned and separated into trials. Standard processing may include PSTH computation aligned to trial onset or other events, and often grouped by different trial types. Neuroscience groups have traditionally developed custom home-made toolchains.

In recent years, several leaders have been emerging as de facto standards with significant community uptake:

Kilosort provides most automation and has gained significant popularity, being adopted as one of the key spike sorting methods in the majority of the teams/collaborations we have worked with. As part of our Year-1 NIH U24 effort, we provide support for data ingestion of spike sorting results from Kilosort. Further effort will be devoted for the ingestion support of other spike sorting methods. On this end, a framework for unifying existing spike sorting methods, named SpikeInterface, has been developed by Alessio Buccino, et al. SpikeInterface provides a convenient Python-based wrapper to invoke, extract, compare spike sorting results from different sorting algorithms.

Key Partnerships

Over the past few years, several labs have developed DataJoint-based data management and processing pipelines for Neuropixels probes. Our team collaborated with several of them during their projects. Additionally, we interviewed these teams to understand their experimental workflow, pipeline design, associated tools, and interfaces. These teams include:

  • Moser Group (Norwegian University of Science and Technology): see pipeline design
  • Andreas Tolias Lab (Baylor College of Medicine)
  • BrainCoGs (Princeton Neuroscience Institute)
  • Brody Lab (Princeton University)

Element Architecture

Each of the DataJoint Elements creates a set of tables for common neuroscience data modalities to organize, preprocess, and analyze data. Each node in the following diagram is a table within the Element or a table connected to the Element.

ephys_acute module

diagram

ephys_chronic module

diagram

ephys_precluster module

diagram

ephys_no_curation module

diagram

subject schema (API docs)

Although not required, most choose to connect the Session table to a Subject table.

Table Description
Subject A table containing basic information of the research subject.

session schema (API docs)

Table Description
Session A table for unique experimental session identifiers.

probe schema (API docs)

Tables related to the Neuropixels probe and electrode configuration.

Table Description
ProbeType A lookup table specifying the type of Neuropixels probe (e.g. "neuropixels 1.0", "neuropixels 2.0 single-shank").
ProbeType.Electrode A table containing electrodes and their properties for a particular probe type.
Probe A record of an actual physical probe.
ElectrodeConfig A record of a particular electrode configuration to be used for ephys recording.
ElectrodeConfig.Electrode A record of electrodes out of those in ProbeType.Electrode that are used for recording.

ephys schema (API docs)

Tables related to information about physiological recordings and automatic ingestion of spike sorting results.

Table Description
ProbeInsertion A record of surgical insertions of a probe in the brain.
EphysRecording A table with metadata about each electrophysiogical recording.
Clustering A table with clustering data for spike sorting extracellular electrophysiology data.
Curation A table to declare optional manual curation of spike sorting results.
CuratedClustering A table with metadata for sorted data generated after each curation.
CuratedClustering.Unit A part table containing single unit information after spike sorting and optional curation.
WaveformSet A table containing spike waveforms for single units.

ephys_report schema (API docs)

Tables for storing probe or unit-level visualization results.

Table Description
ProbeLevelReport A table to store drift map figures generated from each recording probe.
UnitLevelReport A table to store figures (waveforms, autocorrelogram, peak waveform + neighbors) generated for each unit.
QualityMetricCutoffs A table to store cut-off values for cluster quality metrics.
QualityMetricSet A manual table to match a set of cluster quality metric values with desired cut-offs.
QualityMetricReport A table to store quality metric figures.

Element Development

Through our interviews and direct collaboration on the precursor projects, we identified the common motifs to create the Array Electrophysiology Element.

Major features of the Array Electrophysiology Element include:

  • Pipeline architecture detailed by:

    + Probe, electrode configuration compatible with Neuropixels probes and generalizable to other types of probes (e.g. tetrodes) - supporting both chronic and acute probe insertion modes.

    + Probe-insertion, ephys-recordings, LFP extraction, clusterings, curations, sorted units and the associated data (e.g. spikes, waveforms, etc.).

    + Store/track/manage different curations of the spike sorting results - supporting both curated clustering and kilosort triggered clustering (i.e., no_curation).

  • Ingestion support for data acquired with SpikeGLX and OpenEphys acquisition systems.
  • Ingestion support for spike sorting outputs from Kilosort.
  • Triggering support for workflow integrated Kilosort processing.
  • Sample data and complete test suite for quality assurance.

Data Export and Publishing

Element Array Electrophysiology supports exporting of all data into standard Neurodata Without Borders (NWB) files. This makes it easy to share files with collaborators and publish results on DANDI Archive. NWB, as an organization, is dedicated to standardizing data formats and maximizing interoperability across tools for neurophysiology. For more information on uploading NWB files to DANDI within the DataJoint Elements ecosystem see the corresponding notebook on the tutorials page.

To use the export functionality with additional related dependencies, install the Element with the nwb option as follows:

1
pip install element-array-ephys[nwb]

Roadmap

Incorporation of SpikeInterface into the Array Electrophysiology Element will be on DataJoint Elements development roadmap. Dr. Loren Frank has led a development effort of a DataJoint pipeline with SpikeInterface framework and NeurodataWithoutBorders format integrated https://github.com/LorenFrankLab/nwb_datajoint.

Future additions to this element will add functionality to support large (> 48 hours) neuropixel recordings via an overlapping segmented processing approach.

Further development of this Element is community driven. Upon user requests we will continue adding features to this Element.

  1. Jun, J., Steinmetz, N., Siegle, J. et al. Fully integrated silicon probes for high-density recording of neural activity. Nature 551, 232–236 (2017). https://doi.org/10.1038/nature24636. ↩