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= Brain-fingerprinting = | = Multivariate Temporal Response Function = |
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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. | |
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== Plotting the TRF == Drag the EEG/MEG file in the command tab. Select the 'Run' button, then choose 'Plot Temporal Response Function (TRF)'. You will need to set several parameters for the TRF analysis. Specify the data file for the stimulus, indicate the EEG or MEG channels for response analysis, set the range of time lags to explore, and confirm the sampling rate to ensure temporal accuracy. Run the TRF plotting script. Brainstorm computes the TRF and displays it, showing the estimated neural response function over your specified time lags for a chosen channel. |
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'. || {{attachment:Screenshot 2024-07-18 at 1.56.50 PM.png|Screenshot 2024-07-18 at 1.56.50 PM.png}} || {{attachment:Screenshot 2024-07-18 at 2.00.25 PM.png|Screenshot 2024-07-18 at 2.00.25 PM.png}} || |
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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'. {{attachment:Screenshot 2024-07-18 at 2.04.18 PM.png|Screenshot 2024-07-18 at 2.04.18 PM.png|width="80%"}} |
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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'. || {{attachment:Screenshot 2024-07-18 at 2.10.50 PM.png|Screenshot 2024-07-18 at 2.10.50 PM.png}} || {{attachment:Screenshot 2024-07-18 at 2.09.17 PM.png|Screenshot 2024-07-18 at 2.09.17 PM.png}} || |
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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. || {{attachment:Screenshot 2024-07-18 at 2.14.13 PM.png|Screenshot 2024-07-18 at 2.14.13 PM.png}} || {{attachment:Screenshot 2024-07-18 at 2.18.42 PM.png|Screenshot 2024-07-18 at 2.18.42 PM.png}} || In order to extract the data for specific channels, you will need to run the 'Extract Value' process on these output matrices. First, drag one of the matrices into the 'Process1' box. Select 'Run' and then choose 'Extract' > 'Extract Values'. {{attachment:Screenshot 2024-07-18 at 2.21.38 PM.png|Screenshot 2024-07-18 at 2.21.38 PM.png|width="70%"}} Input your preferred analysis parameters including channel number and time window. For this tutorial, we will choose to analyze channel 80. Set these parameters: {{attachment:Screenshot 2024-07-18 at 2.24.44 PM.png||width="70%"}} |
Multivariate Temporal Response Function
Authors: Anna Zaidi, Raymundo Cassani
This tutorial will host the steps to use the mTRF-Toolbox in Brainstorm. ...
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.
In order to extract the data for specific channels, you will need to run the 'Extract Value' process on these output matrices. First, drag one of the matrices 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: