Tutorial: Import and visualize functional NIRS data

<!> This tutorial is under construction <!>

Authors: Thomas Vincent, Zhengchen Cai

The current tutorial assumes that the tutorials 1 to 6 have been performed. Even if they focus on MEG data, they introduce Brainstorm features that are required for this tutorial.

List of prerequisites:

Download

The dataset used in this tutorial is available online.

Presentation of the experiment

Create the data structure

Create a protocol called "TutorialNIRSTORM":

In term of sensor configuration, NIRS is very similar to EEG and the placement of optodes may change from subject to the other.

(!) Should we add (EEG or NIRS) in the interface?

Create a subject called "Subject01" (Go to File -> New subject), with the default options

Import anatomy

Import MRI

Make sure you are in the anatomy view of the protocol.

Right-click on "Subject01 -> Import MRI". Select T1_MRI.nii from the NIRS_sample data folder. Reply "yes" when asked to apply the transformation.

This will open the MRI review panel where you have to set the fudicial points (See Import the subject anatomy).

NIRSTORM_tut1_MRI_edit_v2.gif

Here are the MRI coordinates (mm) of the fudicials used to produce the above figure:

Import Meshes

The head and white segmentations provided in the NIRS sample data were computed with Brainvisa.

Right-click on "Subject01 -> Import surfaces". From the NIRS sample data folder, select files: head_10000V.mesh, hemi_8003V.mesh and white_8003V.mesh.

You can check the registration between the MRI and the loaded meshes by right-clicking on each mesh element and going to "MRI registration -> Check MRI/Surface registration".

NIRSTORM_tut1_new_MRI_meshes.gif

Import NIRS functional data

The functional data used in this tutorial was produced by the Brainsight acquisition software and is available in the NIRS sample folder in S01_Block_FO_LH_Run01.brs. This folder contains the following files:

To import this data set in Brainstorm:

Registration

In the same way as in the tutorial "Channel file / MEG-MRI coregistration", the registration between the MRI and the NIRS is first based on three reference points Nasion, Left and Right ears. It can then be refined with the either the full head shape of the subject or with manual adjustment.

Step 1: Fiducials

Step 2: Head shape

/!\ We don't have digitized head points for this data set. We should skip this

Step 3: manual adjustment

/!\ TODO?

To review this registration, right-click on "Common files / NIRS sensors (96) -> Display sensors"

Show the fiducials, which were stored as additional digitized head points: right-clicj on "Common files / NIRS Sensors (96) -> Digitized head points -> View head points"

NIRSTORM_tut1_display_sensors_fiducials.png

/!\ TOFIX: the registration is buggy

/!\ TOFIX: only the sources are displayed -> also show detectors

As reference, the following figures show the position of fiducials [blue] (inion and nose tip are extra positions), sources [orange] and detectors [green] as they were digitized by Brainsight:

NIRSTORM_tut1_brainsight_head_mesh_fiducials_1.gif NIRSTORM_tut1_brainsight_head_mesh_fiducials_2.gif NIRSTORM_tut1_brainsight_head_mesh_fiducials_3.gif

Review Channel information

The resulting data organization should be:

NIRSTORM_tut1_func_organization.png

This indicates that the data comes from the Brainsight system (BRS) and comprises 96 channels.

To review the content of channels, right-click on "BS channels -> Edit channel file".

[ATTACH]

Visualize NIRS signals

Select "Subject01/S01_Block_FO_LH_Run01/Link to raw file -> NIRS -> Display time series"

It will open a new figure with superimposed channels

NIRSTORM_tut1_time_series_stacked.png

Which can also be viewed in butterfly mode

NIRSTORM_tut1_time_series_butterfly.png

We refer to the tutorial for navigating in these views "Review continuous recordings"

Montage selection

Within the NIRS channel type, the following channel groups are available:

/!\ Add screenshot

Tutorials/NIRSDataImport (last edited 2015-11-13 16:52:33 by ?ThomasVincent)