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Hit 'Run'. A new matrix file will have been created. You can observe the TRF time series by double clicking on it. | Hit 'Run'. A new matrix file containing the weights for the specified channel will have been created. For visualization purposes, you can also double click the file which will open a new window with the TRF time series. |
Multivariate Temporal Response Function
Authors: Anna Zaidi, Raymundo Cassani
This tutorial will host the steps to use the mTRF-Toolbox in Brainstorm. ...
Contents
Introduction
This tutorial introduces the Temporal Response Function (TRF) analysis within the Brainstorm environment, employing the mTRF Toolbox. TRF analysis is instrumental in delineating the dynamics of the brain's response to continuous stimuli, such as speech and music, providing insights into the underlying neural mechanisms.
Install mTRF-Toolbox
In order to use the process files required for TRF analysis, you will need to download the mTRF toolbox.
First, visit the mTRF Toolbox GitHub page to download the latest version of the toolbox. Click the "Code" button and extract the downloaded zip file into a directory that MATLAB can access.
Then, open MATLAB and add the toolbox to your MATLAB path using the addpath function. This ensures MATLAB recognizes the toolbox commands.
Alternatively, you can install the mtrf manually from Brainstorm directly. For that, go to Plug-ins > Statistics > mtrf. Or, the plugin will install automatically once you call the process for the first time.
Preparing the data
Using the Introduction dataset, you will first need to import the entire recordings for whichever run you want to study into your database. Right-click on the raw file, and then 'Import in database'.
Once this is done, the recordings will have appeared in a new file. Some recordings will be labeled as bad and therefore need to be handled. Right-click on the file and select 'Accept Trial'.
Saving the TRF weights
In order to start your TRF analysis, you will need to run the 'Temporal Response Function Analysis' process. First, drag the imported file in the 'Process1' box. Click 'Run', then select 'Encoding' > 'Temporal Response Function Analysis'.
Set the analysis parameters, including the range of time lags to investigate, and the events that you want to analyze. In this tutorial, choose -100ms for minimum time lag, 200ms maximum time lag and we will be looking at the TRF related to deviant and standard beeps. Once your parameters are chosen, hit 'Run'. This will save two files in your database as matrices containing the weights between neural and response data.
Investigating a specific channel
In order to extract the data for specific channels, you will need to run the 'Extract Value' process on these output matrices. First, drag the chosen matrix into the 'Process1' box. Select 'Run' and then choose 'Extract' > 'Extract Values'.
Input your preferred analysis parameters including channel number and time window. For this tutorial, we will choose to analyze channel 80. Set these parameters:
Hit 'Run'. A new matrix file containing the weights for the specified channel will have been created. For visualization purposes, you can also double click the file which will open a new window with the TRF time series.