Analytic Strategies

Here are various analytic strategies that can be used on the data produced by this pipeline. Experimental analyses for the following can be performed in EEGLAB's study structure, which requires splitting subject data into conditions, saved to separate files (detailed in Stage 3 wiki).

Table of Contents Event-related potentials Mass Univariate ERP toolbox Adaptive-factor adjustment (AFA) Spectral measures Source Information Flow Toolbox (SIFT) Measure Projection Analysis

Event-related potentials

Event-related potential (ERP). ERPs are stereotyped changes in EEG amplitude associated with a stimulus.

Mass Univariate ERP toolbox

A Toolbox for mass univariate analysis of whole-scalp (channel-space) ERPs.

Adaptive-factor adjustment (AFA)

AFA performs frame-by-frame ERP analysis in a linear model framework. Can be used in complex multifactorial designs. Can be performed in channel-, IC-, or source-space (Sheu et al., 2016).

Spectral measures

Two common spectral (time/frequency) measures are event-related spectral pertubation (ERSP) and inter-trial coherence (ITC) (Makeig, 1993). ERSPs are stereotyped changes in EEG spectral power associated with a stimulus. ITC measures inter-trial phase coherence of EEG oscillations across a range of frequencies.

Source Information Flow Toolbox (SIFT)

SIFT performs causal analyses of information flow across multiple sources of EEG activity. Can only be performed in IC-space (or ICA-based source-space).

Measure Projection Analysis

Measure Projection Analysis Projects ICs into source-space and clusters ICs/voxels by measure similarity. This is done within- and across-subjects, and can be used with many measures, such as ERP, ERSP, and SIFT.