This page outlines the standard analysis workflow using the ScalpObject class to process, analyze, and visualize scalp-level EEG data. Reference script is runERP.m.

Example

# load in required variables

% Initialize ScalpObject
scalpObject = ScalpObject(project.scalpData, project.info, baselineTime, timeRange, cfg);

% Clean missing subject data
scalpObject = scalpObject.cleanDatasets();

% Preprocess: outlier removal, baseline correction
scalpObject = scalpObject.standardProcessing();

% Calculate average EEG across channels/freqs/time
scalpObject = scalpObject.calChanData();

% Run group comparisons with default cfg
scalpObject = scalpObject.analyzeScalp();

% Plot ERP waveforms across groups - Override cfg and plot Pz and FC4 electrodes only. cfg is used for all other parameters
scalpObject.plotERPs('chans2plot',{'Pz', 'FC4'});

% Plot significant group differences in bar form
scalpObject.plotScalpBar();

📚 Initial Set Up and Processing

obj = ScalpObject(project.scalpData, project.info, baselineTime, timeRange,cfg)

Initializes a new scalp analysis object.

Inputs	Description
scalpData	Struct of EEG data for each group
info	Metadata from project.info
baselineTime	1×2 vector (in ms) for baseline correction
timeRange	Struct defining labeled time windows
cfg (optional)	Configuration struct for filtering/plotting

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obj.cleanDatasets()

Removes subjects missing across any group or variable.

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obj.standardProcessing(...)

Performs outlier removal and optional baseline correction.

Parameter	Description	Default
'outlier'	'5SD' or '3MAD' method for subject-level outlier removal	'5SD'
'calBaseline'	Whether to apply baseline correction	1

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obj.calChanData()

Computes average channel-level activity across frequencies, time windows, and groups.

Parameter	Description
None	No parameters

Main Analysis Functions

⚠️ If no name-value pairs are specified, values in cfg are used by default. Name-value pairs override cfg.

💻 obj.analyzeScalp(...)

Performs group comparisons and identifies significant electrodes.

Parameter	Description
'vars2plot'	Cell array of variable names to include
'freq2plot'	Frequencies to analyze
'times2plot'	Time windows to compare (e.g., 'time1')
'combinations'	Nx2 array of group indices to compare (e.g., [1 2])
'FDRflag'	1 = apply FDR correction; 0 = uncorrected
'toPlot'	1 = generate scalp topoplots
'isnormal'	'auto', 1 = assume normal, 0 = non-parametric test

Uses cfg by default; name-value pairs take precedence.

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obj.calSigTbl(...)

Extracts significantly different neural measures and saves them into a table for each variable and time window. Must be run after obj.analyzeScalp().

Parameter	Description
chanTypes (optional)	A string specifying which channels to include in the table: • 'sig' (default) extracts only significant channels• 'all' includes all channels

Output: Populates obj.results.sigValues.(variable).(time) with the resulting tables.

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📉 obj.plotERPs(...)

Plots ERP waveforms across selected channels, groups, and frequencies.

Parameter	Description
'vars2plot'	Variables to plot
'freq2plot'	Frequency bands to include
'times2plot'	Time windows to plot
'chans2plot'	Channel labels or 'all' for significant channels
'groups2plot'	Groups to overlay in the plot
'errorType'	'none', 'sem', or '95CI'
'color_list'	Custom colors for each group

Significant channels are used if 'chans2plot' = 'all'.

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📊 obj.plotScalpBar(...)

Plots grouped bar charts for selected variables, frequencies, and time ranges.

Parameter	Description
'vars2plot'	Variables to plot
'freq2plot'	Frequency bands to include
'times2plot'	Time windows to plot
'chans2plot'	Channel labels or 'all' for significant channels
'groups2plot'	Groups to overlay in the plot
'color_list'	Custom colors for each group