Chapter 03: Working with STUDY designs

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Arrow.small.left.gif Chapter 02: STUDY Creation
Tutorial Outline
Chapter 04: Data Visualization Tools Arrow.small.right.gif


Contents

Introduction

The STUDY.design structure is a concept introduced in EEGLAB v9. It allows performing statistical comparisons of multiple trial and dataset subsets of a STUDY without creating and storing the STUDY more than once. All the statistical designs are contained in the STUDY structure as (STUDY.design) sub-structures. For instance, a STUDY might contain datasets for 5 conditions comprising a 2x2 set of conditions for each subject plus a 'novel' condition. Data from all five conditions might be used to find clusters of similar independent component sources across subjects. However, statistical comparisons might be targeted to look at the main effects and interactions among the 2x2 conditions only, at differences between the 'novel' condition and each of the other four conditions, etc. This can be handled, beginning in EEGLAB v9, by defining a single STUDY structure with multiple STUDY.design sub-structures.

The main advantages of using STUDY designs are detailed below:

  • No need to have one dataset per condition. An important restriction of working with STUDY structures in EEGLAB 8.0 (prior to STUDY.design) was that to compare multiple conditions users had to generate one dataset per condition. However, to analyze the influence of various contextual information about trials, it may be relatively impractical to generate many datasets with specific sets of trials. The new 'design' scheme in EEGLAB 9.0 is backward compatible with EEGLAB 8 but allows for more flexibility, in particular allowing the STUDY functions to dynamically extract specified data trials from datasets. Each dataset may contain several conditions or several datasets can be merged, using the STUDY design facility, to form to one condition.
  • No restriction to studying "groups" and "conditions" only. Any user-defined independent variable may now be used to contrast different subsets of trials or datasets.
  • The ability to create and analyze different STUDY designs within the same STUDY, each selecting only a subset of independent variable values.

Simple design

Example: For instance in an oddball paradigm comprising trials time locked to oddball, distractor, and standard stimuli, a user might want to contrast oddball and distractor responses, considered together, with responses to standard stimuli. One might also want to look for differences between responses to oddball and distractor stimuli. If this STUDY has two subject groups, the user might want to look at the effect of group on any of the response types, just focus an analysis on one group, or look for Group by Condition interactions. One might also want to temporarily exclude a subject from a data analysis. All of these design concepts can be processed within a single STUDY using multiple STUDY.design structures. Using multiple STUDY.design structures may also be useful for testing different signal processing options. For instance, one might create two identical STUDY designs, in one computing the time/frequency measures using FFTs in one and using wavelets in the other one. Once computed, you will be able to toggle between design results so as to compare them.

Note that the tutorial STUDY for EEGLAB v9 is the same one that has been available in the tutorial since 2006. A default design, implementing EEGLAB processing of the whole STUDY (as per EEGLAB Version 8) is automatically been created when the tutorial STUDY is first loaded. In addition, all the precomputed measure files from v8 are preserved and may be used. If you are importing an EEGLAB STUDY from a version prior to v9 and not using the STUDY design menu, EEGLAB should behave exactly as it did prior to version 9. To edit the STUDY design, simply select the second STUDY menu as shown below. Note that if you change the default design (design(1)), your precomputed measure data files (STUDY ERP, spectrum, ERSP and ITC) may be lost.


Studydesignmenu.jpg


This will pop up the following interface


Studydesign.jpg


The three push buttons at the top may be used to add a new design ("Add design"), rename a given design ("Rename design"), or delete a given design ("Delete design"). Note that the default design (design(1)) cannot be deleted. Adding a design copies the current design and creates a new design names "Design x" (x being the index of the new design).

The "Independent variable 1" list helps define independent variables. Currently, up to two independent variables may be defined (the two left columns). The list of independent variables is automatically generated based on the STUDY definition information and also based on events from each of the datasets. For details on what information from dataset is being extracted, refer to the STUDY design structure tutorial. Once an independent variable is selected, it is possible to select only a subset of its values. All the datasets or trials not selected will simply not be included in the STUDY.design processing. For instance, in this specific example, the independent variable 'condition' may take the values 'non-synonyms' and 'synonyms'. These values may be combined by pressing the "Combine selected value" push button. In this case, since there are only two values of the independent variable "condition", this is irrelevant. The detailed example at the end of this section shows an example of combining two values. Each independent variable also has a pairing status ("paired statistics" for paired data and "unpaired statistics" for unpaired data).

The "Subject" list contains the subjects to include in a specific design. Some subjects may be excluded or included. Note that it is better to select all subjects before pre-computing all STUDY measures, and then to exclude some subjects if necessary. When two groups of subjects are included (patients versus controls, for instance), some STUDY.design instances may include only one category of subjects.

Selecting/excluding specific dataset or trials from design

The "Select only specific dataset/trials" push button to define a list of independent variables and values to include in the design. Clicking on the push button, "Select only specific dataset/trials," pops up the following interface.


Studydesignselect.jpg


In this interface, you may select specific independent variables with specific values to include in the STUDY. This option is only relevant for complex STUDY designs in which some sets of trials and/or datasets are excluded. Pressing the "Add" button will add the selection to the edit box on the right of the "Select only specific dataset/trials" push button in the STUDY design interface.

2-way design

Below we show a more complex STUDY design scheme including 6 designs. In this experiment, there were two groups of subjects, "control" and "nondual" ( a type of meditation practice). There were also four types of stimuli ("blank", "audio", "light" and "both" (audio and light)), two sessions for each subject, and two presentation modes ("evoked" and "spontanous"). Here, the stimulus type "audio - light" is not a real stimulus type; it was obtained by selecting stimuli "audio" and "light" and pressing the "Combine selected values" push button - see design number 3 below for more details. These screen captures are courtesy of the Institute of Noetic Science.

In the first design, we contrast the two groups of subjects for the "audio" and "visual" stimuli. There are two independent variables for this design (a 3x2 design).

Studydesign n0.jpg


In the second design, we only consider the "nondual" group subjects and three types of stimuli ("audio", "light" and "blank"). There is only one independent variable in this design (1x3 design).

Studydesign n1.jpg


Excluding specific subjects

In the third design, we only consider "nondual" subjects and compare two types of stimuli ("blank" versus "audio - light"). The "audio - light" condition groups together both "audio" and "light" trials - i.e. the stimulus may have been of either type "audio" or "light". This design helps contrast brain activity following stimulation compared to when no stimulus was presented ("blank" condition). This is a simple 1x2 design.

Studydesign n2.jpg


Design with custom-defined event

In the fourth design, we were interested in analysing audio stimuli that had been preceded by various types of stimuli. The independent variable "prevevent" had to be defined using a script. A field was added to the event structure using a custom script - it contained the previous stimulus type for each time-locking event. For more information on how to create and modify events in EEGLAB datasets, see this section. Once events are modified, they will be automatically detected at the STUDY level - note that you have to modify events in all datasets included in the design. In case, you already have an existing STUDY, you might have to recreate a new one.

Note that in the design below, the edit box on the right of the "Select only specific datasets/trials" GUI contains the string "'StimulusType', { 'audio' }". It indicates to EEGLAB that it should only consider this type of stimulus in this design and ignore all trials of type "light", "blank" and "both". This is a 1x3 design.

Studydesign n3.jpg


Other examples of STUDY design

In the fifth design, we compared brain responses to "light" and "audio" stimuli in sessions 1 and 2. This is a 2x2 design.

Studydesign n4.jpg


Finally, in the sixth design, we compared brain responses to "light" and "audio" stimuli in "evoked" and "spontaneous" conditions. This is again a 2x2 design.

Studydesign n5.jpg


This simple example shows that the range of possibilities for STUDY designs is large. More details about STUDY.design structure is available in the STUDY structure part of the tutorial.

Note: As of EEGLAB 12, a new row in the STUDY design graphic interface allows selecting a specific folder to store STUDY design files. This prevents encountering conflicts when several studies are pointing to the same datasets. This also allow users to better organize their data.


Arrow.small.left.gif Chapter 02: STUDY Creation
Tutorial Outline
Chapter 04: Data Visualization Tools Arrow.small.right.gif