EegFun.jlEEG/ERP analysis in Julia

using Pkg
Pkg.add("EegFun")

using EegFun

# Load EEG data and layout
dat = EegFun.read_raw_data("your_data.bdf")
layout = EegFun.read_layout("biosemi64.csv")

# Create Eegfun datatype
dat = EegFun.create_eegfun_data(dat, layout)

# Basic preprocessing
EegFun.highpass_filter!(dat, 1)      # High-pass filter at 1 Hz
EegFun.rereference!(dat, :avg)       # Average reference
EegFun.is_extreme_value!(dat, 100)   # Mark extreme values

# Continuous data Browser
EegFun.plot_databrowser(dat)

# Create epochs and compute ERPs
epoch_cfg = [
  EegFun.EpochCondition(name = "Cond1", trigger_sequences = [[1]]),
  EegFun.EpochCondition(name = "Cond2", trigger_sequences = [[2]])
  ]
epochs = EegFun.extract_epochs(dat, epoch_cfg, (-0.2, 0.8))

# Epoch data browser
EegFun.plot_databrowser(epochs[1]) # Cond1

# Plot epochs
EegFun.plot_epochs(epochs, layout = :grid)
EegFun.plot_epochs(epochs, layout = :topo)
EegFun.plot_epochs(epochs, layout = :single, channel_selection = EegFun.channels(:PO7))
EegFun.plot_epochs(epochs, layout = :single, channel_selection = EegFun.channels([:PO7, :PO8]))

# ERPs
erps = EegFun.average_epochs(epochs)

EegFun.plot_erp(erps, layout = :grid)
EegFun.plot_erp(erps, layout = :topo)
EegFun.plot_topography(erps, interval_selection = (0.1, 0.2)) # between 100 and 200 ms