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MRG: Restructure fNIRS IO tutorial #9408

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merged 4 commits into from
May 20, 2021
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Reference issue

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What does this implement/fix?

Reordering and expanding the information in the fNIRS data type tutorial. As its had lots of growth lately but not much structure.

tutorials/io/30_reading_fnirs_data.py Outdated Show resolved Hide resolved
tutorials/io/30_reading_fnirs_data.py Outdated Show resolved Hide resolved
tutorials/io/30_reading_fnirs_data.py Outdated Show resolved Hide resolved
@rob-luke
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@agramfort @drammock @larsoner please merge if happy.

@rob-luke rob-luke changed the title WIP: Restructure fNIRS IO tutorial MRG: Restructure fNIRS IO tutorial May 20, 2021
@larsoner larsoner merged commit 8103451 into mne-tools:main May 20, 2021
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Thanks @rob-luke !

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dang... was in the middle of a review. well, this is as far as I got.

Comment on lines +9 to +25
MNE includes various functions and utilities for reading fNIRS
data and optode locations. Regardless of the manufacturer and file format,
MNE stores both the measurement data and metadata in a consistent manner.

fNIRS devices consist of light sources and light detectors,
often also termed emitter/transmitter and receiver respectively.
A channel is formed by source-detector pairs, and MNE represents the
channel location as the midpoint between source and detector.
MNE stores the location of the channels, sources, and
detectors.
There are a variety of fNIRS data types which can be represented in MNE.
For continuous wave fNIRS data this includes amplitude, optical density,
oxyhaemoglobin, and deoxyhemoglobin.
And for frequency domain fNIRS this additionally includes
AC amplitude and phase.
Different vendors save the data as different data types, and MNE will load
the data as the appropriate type.
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Suggested change
MNE includes various functions and utilities for reading fNIRS
data and optode locations. Regardless of the manufacturer and file format,
MNE stores both the measurement data and metadata in a consistent manner.
fNIRS devices consist of light sources and light detectors,
often also termed emitter/transmitter and receiver respectively.
A channel is formed by source-detector pairs, and MNE represents the
channel location as the midpoint between source and detector.
MNE stores the location of the channels, sources, and
detectors.
There are a variety of fNIRS data types which can be represented in MNE.
For continuous wave fNIRS data this includes amplitude, optical density,
oxyhaemoglobin, and deoxyhemoglobin.
And for frequency domain fNIRS this additionally includes
AC amplitude and phase.
Different vendors save the data as different data types, and MNE will load
the data as the appropriate type.
fNIRS devices consist of two kinds of optodes: light sources (AKA "emitters" or
"transmitters") and light detectors (AKA "receivers"). Channels are defined as
source-detector pairs, and channel locations are defined as the midpoint
between source and detector.
MNE-Python provides functions for reading fNIRS data and optode locations from
several file formats. Regardless of the device manufacturer or file format,
MNE-Python's fNIRS functions will internally store the measurement data and its
metadata in the same way (e.g., data values are always converted into SI
units). Supported measurement types include amplitude, optical density,
oxyhaemoglobin concentration, and deoxyhemoglobin concentration (for continuous
wave fNIRS), and AC amplitude and phase (for frequency domain fNIRS).

@rob-luke rob-luke deleted the fnirsdata branch May 21, 2021 02:56
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4 participants