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‎README.md

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# DataJoint Element - Array Electrophysiology Element
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DataJoint Element for extracellular array electrophysiology.
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DataJoint Elements collectively standardize and automate data collection and analysis for neuroscience experiments. Each Element is a modular pipeline for data storage and processing with corresponding database tables that can be combined with other Elements to assemble a fully functional pipeline.
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DataJoint Element for extracellular array electrophysiology. DataJoint Elements
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collectively standardize and automate data collection and analysis for neuroscience
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experiments. Each Element is a modular pipeline for data storage and processing with
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corresponding database tables that can be combined with other Elements to assemble a
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fully functional pipeline.
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![diagram](https://raw.githubusercontent.com/datajoint/element-array-ephys/main/images/diagram_flowchart.svg)
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Installation and usage instructions can be found at the
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[Element documentation](datajoint.com/docs/elements/element-array-ephys).
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![element-array-ephys diagram](https://raw.githubusercontent.com/datajoint/element-array-ephys/main/images/attached_array_ephys_element_acute.svg)

‎docs/mkdocs.yaml

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ratings:
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name: This page was helpful
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data: 1
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Thanks for your feedback!
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data: 0
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Thanks for your feedback!
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version:
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provider: mike
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social:
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link: https://www.datajoint.com/
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link: https://support.djneuro.io/portal/en/home
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link: https://www.datajoint.com
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name: DataJoint
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link: https://www.linkedin.com/company/datajoint
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link: https://twitter.com/DataJointIO
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link: https://github.com/datajoint
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link: https://hub.docker.com/u/datajoint
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name: DockerHub
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link: https://pypi.org/user/datajointbot
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name: PyPI
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link: https://stackoverflow.com/questions/tagged/datajoint
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extra_javascript:
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- https://js-na1.hs-scripts.com/23133402.js # HubSpot chatbot

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‎docs/src/index.md

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# Element Array Electrophysiology
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This Element features DataJoint schemas for analyzing extracellular array electrophysiology data acquired with Neuropixels probes and spike sorted using Kilosort spike sorter. Each Element is a modular pipeline for data storage and processing with corresponding database tables that can be combined with other Elements to assemble a fully functional pipeline.
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This Element features DataJoint schemas for analyzing extracellular array
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electrophysiology data acquired with Neuropixels probes and spike sorted using Kilosort
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spike sorter. Each Element is a modular pipeline for data storage and processing with
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corresponding database tables that can be combined with other Elements to assemble a
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fully functional pipeline.
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![diagram](https://raw.githubusercontent.com/datajoint/element-array-ephys/main/images/diagram_flowchart.svg)
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The Element is comprised of `probe` and `ephys` schemas. Several `ephys` schemas are
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developed to handle various use cases of this pipeline and workflow:
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The Element is comprised of `probe` and `ephys` schemas. Several `ephys` schemas are developed to handle various use cases of this pipeline and workflow:
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+ `ephys_acute`: A probe is inserted into a new location during each session.
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+ `ephys_chronic`: A probe is inserted once and used to record across multiple sessions.
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+ `ephys_precluster`: A probe is inserted into a new location during each session. Pre-clustering steps are performed on the data from each probe prior to Kilosort analysis.
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+ `ephys_no_curation`: A probe is inserted into a new location during each session and Kilosort-triggered clustering is performed without the option to manually curate the results.
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Visit the [Concepts page](./concepts.md) for more information about the use cases of `ephys` schemas and an explanation of the tables. To get started with building your own data pipeline, visit the [Tutorials page](./tutorials.md).
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+ `ephys_chronic`: A probe is inserted once and used to record across multiple
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sessions.
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+ `ephys_precluster`: A probe is inserted into a new location during each session.
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Pre-clustering steps are performed on the data from each probe prior to Kilosort
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analysis.
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+ `ephys_no_curation`: A probe is inserted into a new location during each session and
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Kilosort-triggered clustering is performed without the option to manually curate the
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results.
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Visit the [Concepts page](./concepts.md) for more information about the use cases of
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`ephys` schemas and an explanation of the tables. To get started with building your own
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data pipeline, visit the [Tutorials page](./tutorials.md).
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### `ephys_acute` module
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![element-array-ephys-acute diagram](https://raw.githubusercontent.com/datajoint/element-array-ephys/main/images/attached_array_ephys_element_acute.svg)
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![element-array-ephys-acute diagram]
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(https://raw.githubusercontent.com/datajoint/element-array-ephys/main/images/attached_array_ephys_element_acute.svg)
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### `ephys_chronic` module
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![element-array-ephys-chronic diagram](https://raw.githubusercontent.com/datajoint/element-array-ephys/main/images/attached_array_ephys_element_chronic.svg)
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![element-array-ephys-chronic diagram]
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(https://raw.githubusercontent.com/datajoint/element-array-ephys/main/images/attached_array_ephys_element_chronic.svg)
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### `ephys_precluster` module
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![element-array-ephys-precluster diagram](https://raw.githubusercontent.com/datajoint/element-array-ephys/main/images/attached_array_ephys_element_precluster.svg)
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![element-array-ephys-precluster diagram]
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(https://raw.githubusercontent.com/datajoint/element-array-ephys/main/images/attached_array_ephys_element_precluster.svg)

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