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1. Core NWB | ||
=========== | ||
1. NWB Conversions | ||
================== | ||
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First, we need to understand what types of data go into NWB. The goal of NWB | ||
is to package all of the data in a particular session into a single file. | ||
The goal of NWB is to package experiment data with the metadata necessary to | ||
analyze the data. All of the data in a particular session goes into a single file. | ||
This includes the neurophysiology data itself, but also includes other data such | ||
as information about the data acquisition, experiment design, experimental subject, | ||
and behavior of that subject. The NWB core schema defines data containers for | ||
the most common data objects in neurophysiology data. The NWB core currently covers | ||
the following experiment types: intracellular electrophysiology (e.g. patch clamping), extracellular | ||
electrophysiology (e.g. Neuropixel probes), and optical physiology (e.g. two-photon imaging). | ||
common data objects in neurophysiology data, including: intracellular | ||
electrophysiology (e.g. patch clamping), extracellular electrophysiology | ||
(e.g. Neuropixel probes), and optical physiology (e.g. two-photon imaging), and behavior. | ||
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.. image:: /img/nwb_overview.png | ||
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All of these data types and relationships are defined using | ||
`HDMF <https://hdmf-schema-language.readthedocs.io/en/latest/>`_, | ||
a specification language for describing complex structures of data. NWB is faced with the challenge | ||
of supporting a large variety of different experiment types, so the data types and relationships | ||
can get quite complex. For this reason the NWB development team provides APIs to help users easily | ||
and efficiently read and write NWB files. These APIs are described in the next section. | ||
All of these data types and relationships are defined in the | ||
`NWB Schema <https://nwb-schema.readthedocs.io/>`_ using the | ||
`HDMF specification language <https://hdmf-schema-language.readthedocs.io/en/latest/>`_. | ||
NWB is faced with the challenge of supporting a large variety of different experiment | ||
types, so the data types and relationships can get quite complex. For this reason the | ||
NWB development team provides APIs to help users easily and efficiently read and | ||
write NWB files. | ||
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The following sections start with the most automated and convenient approaches | ||
and proceed to more involved and customizable solutions. |
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# 2. Automatic NWB Conversions using NeuroConv | ||
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[NeuroConv](https://neuroconv.readthedocs.io/) is a library for automatic conversions from proprietary formats to NWB. | ||
A gallery of all supported formats can be found | ||
[here](https://neuroconv.readthedocs.io/en/main/conversion_examples_gallery/conversion_example_gallery.html). | ||
If NeuroConv supports your source data format, this is the recommended approach, because it is easiest to | ||
implement and automatically helps you adhere to best practices. For advanced usage of NeuroConv, including creating | ||
conversions of ensembles of multiple data streams, see the | ||
[NeuroConv User Guide](https://neuroconv.readthedocs.io/en/main/user_guide/user_guide.html). | ||
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Although NeuroConv supports many common formats, it may not support every type of source data you need. | ||
If your source format is likely to be a common need in the community, for example the output of an acquisition | ||
system or a popular data processing package, please use | ||
[this form](https://github.com/catalystneuro/neuroconv/issues/new?assignees=&labels=enhancement%2Cdata+interfaces&template=format_request.yml&title=%5BNew+Format%5D%3A+) | ||
to request support for this format. On the other hand, some data formats can be ad-hoc, particularly data about task and | ||
behavior. In this case, proceed to the next section for detailed tutorials on using the PyNWB API to manually add this | ||
data to the NWB file. |
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