User Tutorial:Configuring Online Feedback

This tutorial step assumes that you have performed and analyzed an initial session. Now you are going to create a subject-specific parameter configuration for on-line feedback.

Starting up BCI2000

Start BCI2000 using the appropriate batch file at batch/CursorTask_<YourAmplifier>.bat. You might consider creating a link to this file on the desktop.

Subject-Specific Parameters

Now, we will construct a full parameter file that is specific to that subject:

• In the configuration window, click "Load Parameters", and load the system-specific parameter file saved previously at parms/fragments/<YourSystem>.prm.
• Again, click "Load Parameters" to load parms/mu_tutorial/MuFeedback.prm.
• When you have a separate monitor for experimenter and subject, load the parameter file at parms/fragments/stdlib/DualMonitor.prm.
  • In your system's display properties configuration, make sure that the subject's monitor is configured to be located to the right of the main monitor.
  • Make sure the WindowLeft parameter matches the main monitor's actual pixel width.
  • You may need to adapt WindowTop, WindowWidth, and WindowHeight parameters as well; click "Set Config" to try the effect of your changes.
• In the Storage tab:
  • Change the SubjectName field to the subject's initials.
  • Make sure the SubjectSession field is set to 002 and SubjectRun is set to 01.

The Spatial Filter

The Spatial Filter computes a weighted combination of the incoming data from the electrodes based on their placement on the scalp of the subject.

Because we are targeting specific areas of the brain to monitor, we use a spatial filter that allows the program to identify when the electrode of interest is activating specifically.

This is done by subtracting the average of the surrounding electrodes' data from the electrode of interest. For example, as seen to the right the output channel C3_OUT is the data from C3 minus one-quarter each of F3, T7, Cz, and Pz. Such a filter is called a "Laplacian filter".

The Classifier Matrix

The Classifier Matrix applies weights to the incoming data that allows the program to accurately identify Mu Rhythm signals. This is opened by selecting Edit Matrix next to the Classifier parameter in the Filtering tab.

• Set Number of columns to 4, and Number of rows to 1. Click Set new matrix size to apply your changes.
• In the first column (of the first row), labeled input channel, enter C3_OUT if the right hand are being used, C4_OUT for the left hand, or Cz_OUT for the feet.
  • If both hands are being used, set Number of rows to 2, and click Set new matrix size. Enter C3_OUT under input channel in the first row, and C4_OUT in the second.
• In the second column, labeled input element (bin), enter feedback frequency in Hz, immediately followed with Hz, as in 12Hz.
• In the third column, enter the value 2. This corresponds to the control channel for vertical control of the cursor.
• In the fourth column, enter 1 as the weight. For further calibration, this weight can be increased to give stronger control or decreased to give finer control.
• Finally, save your configuration in a parameter file wherever you find appropriate.

Performing Mu Rhythm Feedback Sessions

Proper calibration of the Classifier and Spatial matrices are what take the most time. A Mu Rhythm Feedback Session should be performed with the classifier matrix to gauge the efficacy of the settings. In the next step, you will learn how to actually perform a Mu rhythm feedback session using this configuration.

See also

User Tutorial:Mu Rhythm BCI Tutorial, User Reference:LinearClassifier