Detecting Pre-Stimulus Source-Level Effects on Object Perception with Magnetoencephalography

This article describes how to set up an experiment that allows detecting pre-stimulus source-level influences on object perception using magnetoencephalography (MEG). It covers stimulus material, experimental design, MEG recording, and data analysis.

Transcript

This method allows fast and transient changes in brain connectivity to be captured before objects are viewed, and the influence of these changes on object perception. The main advantage of MEG over EEG is that the brain's magnetic field is unperturbed by the head, enabling higher-resolution source reconstruction and better connectivity estimates. Begin by recording one minute of empty-room MEG data at one kilohertz.

Monitor the signals from the 102 magnetometers and 204 orthogonally placed planar gradiometers at 102 different positions by visualizing all signals in real time on the acquisition computer. You're not gonna sue us? And here-Next, obtain informed consent from the participant in accordance with the declaration of Helsinki and have them sign the form which includes a statement allowing the processing of personal data.

Is there any metal object from your body? But you can do this when you're inside as well. Next, provide them with non-magnetic clothes and make sure they have no metallic objects in or on their bodies.

Ask them to fill out an anonymous questionnaire to ensure this and to assure they do not have any other exclusion criteria and to document details such as handedness and level of rest. All right, perfect, thank you.Here. Seat the participant on a non-ferromagnetic chair and then attach five head position indicator coils to the head with adhesive, two above one eye, one above the other eye, and one behind each ear.

Place the tracker sensor for the digitization system firmly on the participant's head and fix it to the spectacles for maximum stability. Next, digitize the anatomical landmarks, the left and right pre-auricular points and the nasion, and assure that the pre-auricular points are symmetrical. Also, digitize the five HPI coil positions using a 3D digitizer stylus.

Now, digitize up to 300 points along the scalp and maximize the coverage of the head shape. Cover the well-defined areas of the scalp on MR images, above the inion on the back and the nasion on the front, as well as the nasal bridge. These points will be used for co-registration to an anatomical image.

At this point, remove the spectacles with the tracker sensor and attach disposable electrodes above and below the right eye to monitor vertical eye movements. Also attach electrodes to the right of the right eye and to the left of the left eye to monitor horizontal eye movements. Attach additional electrodes below the right collarbone and below the heart to monitor heart rate.

The signal in these areas is robust, so checking the impedance is not necessary. Also, attach an electrode as a ground below the neck.Please. Now, escort the participant to the MEG shielded room and instruct them to sit in the MEG chair.

Plug the HPI wiring harness and the disposable electrodes in the MEG system. Then raise the chair such that the participant's head touches the top of the helmet and assure the participant is comfortable. Is this okay now?

Yes.Perfect.Begin by instructing the participant to passively stare at an empty screen for five minutes while recording resting-state MEG data at one kilohertz. Keep the sampling rate at one kilohertz throughout the experiment. Then instruct the participant of the task requirements and have them perform 20 practice trials.

So now we'll go and have a practice session and make sure that everything is okay.Okay. All right? Start the experiment by first displaying instructions, telling the participant which button to press when they see faces and which button to press when they see a vase.

Create a single trial with four events which will apply to all trials in this order:fixation cross, Rubin image, mask, and response prompt. At the beginning of each block, before the task starts, start measuring MEG data and record the initial position of the participant's head position with respect to the MEG. Be sure to monitor the participant via video during the experiment.

In the MEG system, click Go to start. When the dialog asks if the HPI data is to be omitted or added to the recording, inspect the HPI coils signal, and click Accept to record that initial head position. After that, click Record raw to start recording MEG data.

At the beginning of each trial, display the fixation cross for a variable time period of one to 1.8 seconds. Then, display the Rubin image for 150 milliseconds. Next, remove the Rubin image and display the mask for 200 milliseconds, followed by a question prompting the participant to respond within two seconds.

Program the response period such that if participants respond within two seconds, the next trial begins. Otherwise, start the next trial after two seconds. Save the timing of all four events as well as the response choice and its timing.

Monitor the MEG signals by visualizing them in real time on the acquisition computer. When the experiment is complete, escort the participant out of the shielded room and help them detach the sensors. Analyze the acquired data by performing time-frequency analysis on both regions of interest separately from the two trial types using the code seen on the screen here.

First, implement multi-taper time-frequency transformation based on multiplication in the frequency domain. Also, set the taper option to dpss to use a discrete prolate spheroidal sequences function taper and define the frequencies of interest from eight to 13 hertz. Next, set the width of the time window to 200 milliseconds and the smoothing parameter to four hertz.

Set the keeptrials option to yes to return the time-frequency estimates of the single trials. Set the output to fourier to return the complex Fourier spectra. Perform a connectivity analysis on the resulting time-frequency data using the code seen onscreen here, using the settings shown to return the imaginary part of coherency.

Repeat the procedure for each participant before averaging the coherence spectra across frequencies and participants and plotting the resulting grand-averaged imaginary coherency values as a function of time. Here, we see an example trial structure and raw data. A trial starts with the display of a fixation cross.

After one to 1.8 seconds, the Rubin stimulus appears for 150 milliseconds, followed by a mask for 200 milliseconds. A response screen then appears to prompt participants to respond with face or vase. Above, we see multi-channel raw data from an example participant, time-locked to stimulus onset and averaged across trials.

This data in the pre-stimulus analysis window will be the target interval for analysis. Here, we see spectral power estimates from source-localized fusiform face area signals on face and vase trials. This figure shows the imaginary part of coherency between source-localized visual cortex and fusiform face area signals in face and vase trials, in the frequency range of eight to 13 hertz.

Shaded regions represent the standard error of the mean for within-subjects design. MEG is a passive method, much like the pickup of an electric guitar. The machine also bears the risk of being damaged by participants, unlike other modalities.

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Journal (Neuroscience)

Journal (Neuroscience)

Detecting Pre-Stimulus Source-Level Effects on Object Perception with Magnetoencephalography

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