= Multivariate Temporal Response Function = ''Authors: Anna Zaidi, Raymundo Cassani'' This tutorial introduces the Temporal Response Function (TRF) analysis within the Brainstorm environment, employing the [[https://github.com/mickcrosse/mTRF-Toolbox|mTRF-Toolbox]] as plugin. <> == Introduction == Temporal Response Function (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. The present tutorial will show the TRF analysis functionality within the Brainstorm interface using the [[https://github.com/mickcrosse/mTRF-Toolbox|mTRF-Toolbox]] as plugin. For a detailed documentation, more examples and citation for the mTRF-Toolbox, please refer to the [[https://github.com/mickcrosse/mTRF-Toolbox|mTRF-Toolbox GitHub page]]. This tutorial uses data from the [[https://neuroimage.usc.edu/brainstorm/DatasetIntroduction|introduction dataset]], and can be followed by completing all steps of the [[https://neuroimage.usc.edu/brainstorm/Tutorials#Get_started|Get Stared]] tutorials up to and including [[https://neuroimage.usc.edu/brainstorm/Tutorials/PipelineEditor|tutorial 9]]. == Install mTRF-Toolbox == Install '''mTRF-Toolbox''' as a [[https://neuroimage.usc.edu/brainstorm/Tutorials/Plugins|Brainstorm plugin]]. In the main Brainstorm window, go to the menu <
> '''Plug-ins > Statistics > mtrf > Install'''. 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. e.g., '''Run01''' 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}} || Once this is done, the recordings will have appeared in a new file '''Raw (0.00s,360.00s)'''. If the [[https://neuroimage.usc.edu/brainstorm/Tutorials/ArtifactsDetect|bad segments were already identified]] in the continuous recording, the new file will be labeled as '''bad''' (), before continuing we need to change its status to '''good'''. 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%"}} == TRF analysis == 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}} || In this tutorial, we want to compute the TRF the MEG sensors, in a window from -100 to 200 ms after the tones. To do so set the analysis parameters, as follows: Set '''MEG''' for the Thus, set '''-100ms''' for 'minimum time lag', '''200ms''' for 'maximum time lag' and we will be looking at the TRF related to '''deviant''' and '''standard''' tones. Once your parameters are chosen, hit '''Run'''. Once the process finishes, there will be new two matrix files in your database, these contain 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}} || For visualization purposes, you can also double click the matrix files to open a new window with the TRF time series for all the sensors. == Investigating a specific channel == In order to extract the data for specific channels, you will need to run the process '''Extract Value''' on these output matrices. First, drag the chosen matrix 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''' (sensor '''MLP22'''). Set these parameters: {{attachment:Screenshot 2024-07-18 at 2.24.44 PM.png|Screenshot 2024-07-18 at 2.24.44 PM.png|width="60%"}} Click on '''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. {{attachment:Screenshot 2024-07-18 at 2.27.04 PM.png|Screenshot 2024-07-18 at 2.27.04 PM.png}}