Epoching & Event Handling#

Analyze event-related potentials and create epochs from your Wearable Sensing continuous recordings.

Prerequisites

Your data is likely to include event markers in the ‘Trigger’ channel (sent from the Triggerhub or an MMBT-S device). Data should be filtered and cleaned with ICA if needed.

Viewing Events#

If your Wearable Sensing recording includes event markers (triggers from the device), you can view them in MNELAB:

  1. Events appear in the info panel if present in the EDF file

  2. Edit → Events to view all event markers

  3. Events show timestamp and event codes

Importing Events from Separate Files#

If events are stored in a separate file (common with FIF format):

  1. File → Import events

  2. Select the event file (e.g., .fif or .eve format)

  3. Click Open

  4. Events will now appear in the info panel

Creating Epochs#

To analyze time-locked responses:

  1. Tools → Create epochs

  2. Configure parameters:

    • Event type: Select trigger codes of interest

    • Time window: e.g., -0.2 to 1.0 seconds

    • Baseline: e.g., -0.2 to 0 seconds

  3. Click Create

Epoch Parameters

  • Time window: Defines the time range around each event

  • Baseline: Period used for baseline correction (typically pre-stimulus)

  • Event codes: Can select multiple codes or specific values

Dropping Bad Epochs#

Remove epochs with excessive artifacts:

  1. Tools → Drop bad epochs

  2. Configure rejection criteria:

    • Activate Reject: Check this box

    • Enter threshold: e.g., 0.0001 (corresponding to 100 uV peak-to-peak)

  3. Click OK

Epochs exceeding the threshold will be automatically rejected.

Visualizing Evoked Responses#

Butterfly Plots#

View averaged evoked potentials across all channels:

  1. Plot → Plot evoked

  2. Select event types of interest

  3. Optional settings:

    • Spatial colors: Color-code channels by location

    • GFP: Show Global Field Power

  4. Click OK

Separate butterfly plots will appear for each event type.

Topographic Maps#

Create topomaps showing spatial distribution at specific time points:

  1. Plot → Plot evoked topomaps

  2. Select event type

  3. Choose time points:

    • Automatic: Based on peaks

    • Manual: Enter specific times (e.g., “-0.2, 0.1, 0.4”)

  4. Click OK

Joint Plots#

Combine butterfly plots with topomaps:

  1. Plot → Plot evoked

  2. Select event type

  3. Enable:

    • GFP: Show Global Field Power

    • Spatial colors: Color-coded channels

    • Topomaps: Set to “Peaks” for automatic time selection

  4. Click OK

Topomaps will show at the three largest GFP peaks.

Comparing Conditions#

Directly compare evoked responses between different event types:

  1. Plot → Plot evoked comparison

  2. Select channels to compare (e.g., frontal channels for auditory responses)

  3. Select event types to compare

  4. Choose Combine channels: mean or individual

  5. Click OK

Shaded ribbons represent 95% confidence intervals.

Channel Selection for Comparisons

Use Plot → Plot channel locations to identify channel groups (frontal, central, parietal, etc.) before creating comparison plots. This helps you select appropriate channels for your analysis.

Individual Epoch Inspection#

View individual trials before averaging:

  1. Plot → Plot epochs to view individual trials

  2. Plot → Plot image for a 2D representation across trials

Exporting Epochs#

Save epochs for further analysis:

  1. File → Export

  2. Choose format:

    • FIF: For MNE-Python scripts

    • CSV: For custom analysis in other software

Power Spectral Density#

Analyze frequency content of your epochs:

  1. Plot → Plot power spectral density

  2. Configure settings:

    • Frequency range: e.g., 0.5 - 50 Hz

    • Method: Welch (default)

  3. View the PSD plot showing power across frequencies

Next Steps#

After creating epochs from your Wearable Sensing data:

  1. Compute ERPs by averaging: Tools → Average epochs

  2. Export epochs: File → Export (choose FIF for MNE-Python compatibility)

  3. Advanced analysis in MNE-Python for statistics and source localization

Resources#