I.6: Data Averaging

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Arrow.small.left.gif (MT) I.5: Extracting Data Epochs
Tutorial Outline
(MT) Chapter 07: Selecting Data Epochs Arrow.small.right.gif

Contents

Data averaging

Previously (Makeig et al., 2002, 2004), we have discussed ways in which the event-related EEG dynamics occurring in a set of data epochs time locked to some class of events are not limited to nor completely expressed in features of their time-locked trial average or Event-Related Potential (ERP). EEGLAB contains several functions for plotting 1-D ERP averages of dataset trials (epochs). EEGLAB also features functions for studying the EEG dynamics expressed in the single trials, which may be visualized, in large part, via 2-D (potential time series by trials) ERP-image transforms of a dataset of single-trial epochs (a.k.a., epoched data). In ERP-image plots, EEG data epochs (trials) are first sorted along some relevant dimension (for example, subject reaction times, within-trial theta power levels, mean voltage in a given latency window, alpha phase at stimulus onset, or etc.), then (optionally) smoothed across neighboring trials, and finally color-coded and visualized as a 2-D rectangular color (or monochrome) image. (Construction of ERP images will be detailed in section I.8).

Plotting the ERP data on a single axis with scalp maps

Here, we will use the tutorial dataset as it was after the last Key Step, Key Step 8.

Exploratory Step: Plotting all-channel ERPs.

To plot the (ERP) average of all dataset epochs, plus ERP scalp maps at selected latencies, select Plot > Channel ERPs> With scalp maps. As a simple illustration using the sample dataset, we retain the default settings in the resulting pop_timtopo.m window, entering only a plot title and pressing OK.
Pop timtopo.png
A timtopo.m figure (below) appears. Each trace plots the averaged ERP at one channel. The scalp map shows the topographic distribution of average potential at 430 ms (the latency of maximum ERP data variance). Alternatively, one or more exact scalp map latencies may be specified in the pop-window above.
Erpplot1.png
Function timtopo.m plots the relative time courses of the averaged ERP at all channels, plus ‘snapshots’ of the scalp potential distribution at various moments during the average ERP time course. Note that to visualize the ERP scalp map at all latencies -- as an ERP movie (i.e., to view the play of the ERP on the scalp), call function eegmovie.m from the command line.

Plotting ERP traces in a topographic array

Exploratory Step: Plotting ERPs in a Topographic Map.

Here we will plot the ERPs of an epoched dataset as single-channel traces in their 2-D topographic arrangement. Select Plot > Channel ERPs > In scalp array/rect. array. Using the default settings and pressing OK in the resulting pop_topoplot.m window (below)
Pop plottopo.png
produces the following plottopo.m figure.
Erpplot2.png
Note that if called from the command line, the plottopo.m function geom option can also be used to plot channel waveforms in a rectangular grid. You may visualize a specific channel time course by clicking on its trace (above), producing a pop-up sub-axis view. For example, click on the ERP trace marked POz (above) to call up a full-sized view of this trace (as below).
Zoom1.png
Many EEGLAB plotting routines use the toolbox function axcopy.m to pop up a sub-axis plotting window whenever the users clicks on the main plot window. Sub-axis windows, in turn, do not have axcopy.m enabled, allowing the user to use the standard Matlab mouse 'Zoom In/Out' feature.

Plotting ERPs in a two column array

Exploratory Step: Plotting ERPs in a Column Array.

To plot (one or more) average ERP data traces in two column array, select menu item Plot > Channel ERPs > In scalp/rect. array. To use the default settings in the resulting pop_topoplot.m window, check the "Plot in rect. array" checkbox and press OK.
Pop topoplotRectArray.png
The resulting pop_topoplot.m figure (below) appears.
Erpplot3.png
As in the previous plot, clicking on a trace above pops up a full window sub-axis view.

Plotting an ERP as a series of scalp maps

Plotting a series of 2-D ERP scalp maps

Here we will plot ERP data for a series of 2-D scalp maps representing potential distributions at a selected series of trial latencies.

Exploratory Step: Plotting a series of 2-D ERP Scalp Maps.

Select Plot > ERP map series > In 2-D. In the top text box of the resulting pop_topoplot.m window (below), type the epoch latencies of the desired ERP scalp maps.
Note that in this or any other numeric text entry box, you may enter any numeric Matlab expression. For example, instead of 0 100 200 300 400 500, try 0:100:500. Even more complicated expressions, for example -6000+3*(0:20:120), are interpreted correctly.
641pop topoplot.png
The topoplot.m window (below) then appears, containing ERP scalp maps at the specified latencies. Here, the plot grid has 3 columns and 2 rows; other plot geometries can be specified in the gui window above via the Plot geometry text box.
2dscalpmap.png

Plotting ERP data as a series of 3-D maps

Exploratory Step: Plotting a series of 3-D ERP scalp maps.

To plot ERP data as a series of 3-D scalp maps, go to the menu Plot > ERP map series > In 3-D The query window (below) will pop up, asking you to create and save a new 3-D head map 3-D spline file. This process must be done only once for every montage (and proceeds much more quickly in EEGLAB v4.6-). Click OK to begin this process.
3Dscalpmessage.png
The window below will pop up. Here, you have two choices: If you have already generated a spline file for this channel location structure, you may enter it here in the first edit box (first click on the Use existing spline file or structure to activate the edit box, then browse for a datafile. If you have not made such a file, you will need generate one.

However, first your channel locations must be co-registered with the 3-D head template to be plotted. Note that if you are using one of the template channel location files, for example, the (v4.6+) tutorial dataset, the Talairach transformation matrix field (containing channel alignment information) will be filled automatically. Enter an output file name (in the second edit box), trial latencies to be plotted (0:100:500 below indicating latencies 0, 100, 200, 300, 400, and 500 ms) and press OK.
Pop headplot3.png
Now, the 3-D plotting function pop_headplot.m, will create the 3-D channel locations spline file. A progress bar will pop up to indicate when this process will be finished. When the 3-D spline file has been generated, select Plot > ERP map series > In 3-D. Now that a spline file has been selected, another gui window will appear. As for plotting 2-D scalp maps, in the first edit box type the desired latencies, and press OK. The headplot.m figure (below) will appear.
642headplot.jpg
As usual, clicking on a head plot will make it pop up in a sub-axis window in which it can be rotated using the mouse. Note that to select (for other purposes) a head plot or other object in a figure that has the axcopy.m pop-up feature activated, click on it then delete the resulting pop-up window.

To plot the heads at a specified angle, select the Plot > ERP map series > In 3-D menu item. Note that now by default the function uses the 3-D spline file you have generated above. Enter latencies to be displayed and the headplot.m 'view' option (as in the example below), and press OK.
Pop headplot2.png
The headplot.m window (below) will then appear. You may also rotate the individual heads using the mouse. This is often necessary to show the illustrated spatial distribution to best effect.
642headplot view.jpg
We will now briefly describe the channels-to-head model co-registration process. If your dataset contains specific channel locations, for example locations that you may have measured on the subject head using a Polhemus system, and you want to use these electrode locations for 3-D plotting, headplot.m must first determine the positions of your electrode locations relative to a template head surface. A generic transformation cannot be performed because the origin ([0 0 0]) in your electrode location system does not necessarily correspond to the center of the template head (.e.g., the intersection of the fiducial points: nasion and pre-auricular points) used by headplot.m. Even if this were the case, heads have different shapes, so your scanned electrode locations might need to be scaled or warped in 3-D to match the template head mesh.

The co-registration window begins this operation. Call back the headplot.m. gui window using menu item Plot > ERP map series > In 3-D. Set the checkbox labeled Or recompute a new spline file named:, and then click the Manual coreg. push button. A window appears explaining how to perform the co-registration.
Coregister.gif
Pressing OK will cause the co-registration window below to open.
Coregister2.gif
In the window above, the red electrodes are those natively associated with the template head mesh. Rather than directly aligning your electrode locations (shown in green) to the head mesh, your montage will be aligned to template electrode locations associated with the head mesh by scanning on the same subject's head (here shown in red). For the sample dataset, this alignment has already been performed. (Click the Labels on push button to display the electrode labels).

When you have finished the co-registration, simply click OK and a vector of 9 new channel alignment values (shift, in 3-D; rotation, in 3-D; scaling, in 3-D) will be copied back to the interactive headplot.m window. For more information about channel co-registration, see the DIPFIT tutorial.

Note that it is possible, and relatively easy, to generate custom headplot.m head meshes. Let us know by email if you are interested in learning how to do this.

The next tutorial section will demonstrate how to use EEGLAB functions to compare the ERP trial averages of two datasets.


Arrow.small.left.gif (MT) I.5: Extracting Data Epochs
Tutorial Outline
(MT) Chapter 07: Selecting Data Epochs Arrow.small.right.gif