EegFun

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Plot Topography ​

This demo demonstrates creating topographic scalp maps to visualize the spatial distribution of EEG activity at specific time points.

What are Topographic Maps? ​

Topographic maps (topoplots) show the spatial distribution of electrical activity across the scalp:

  • Color-coded amplitudes: Activity levels represented by color

  • Interpolated surfaces: Smooth maps between discrete electrode positions

  • Time-specific snapshots: Activity at particular latencies or time intervals

Interpolation Methods ​

:thin_plate: Thin-plate spline (default; smooth, natural-looking)

:nearest: Nearest neighbor (no interpolation, fastest)

:shepard: Inverse distance weighting

:multiquadratic: Radial basis function

:spherical_spline: Spherical spline (accounts for head curvature)

Note: All interpolation methods except :spherical_spline are implemented using the ScatteredInterpolation.jl package. The spherical spline method uses a custom implementation based on Perrin et al. (1989).

Interpretation ​

Focal activity:

  • Localized color patches suggest specific neural sources

  • Sharp gradients indicate nearby sources

Widespread activity:

  • Diffuse patterns suggest distributed processing

  • Gradual transitions indicate distant or multiple sources

Polarity conventions:

  • Warm colors (red/yellow): Positive voltage

  • Cool colors (blue): Negative voltage

  • Convention may vary by field

Use Cases ​

Visualize ERP components:

  • Show spatial distribution of P1, N170, P300, etc.

  • Identify component topographies

Compare conditions:

  • Side-by-side condition comparisons

  • Difference topographies (condition A - B)

Publication figures:

  • High-quality scalp maps

  • Customizable appearance

  • Multiple time points or conditions

Customization Options ​

Interpolation:

  • Method selection

  • Grid resolution (gridscale)

Appearance:

  • Colormap selection

  • Color limits (ylim)

  • Head outline radius

Labels and markers:

  • Electrode positions

  • Channel labels

  • Font sizes and colors

Colorbar:

  • Position and orientation

  • Size and tick labels

  • Show/hide per plot

Working with Different Data Types ​

Continuous data: Average over time interval

Epoched data: Specify epoch number and time interval

ERP data: Average directly (already averaged)

Workflow Summary ​

This demo shows topographic visualization workflows:

Basic Continuous Data ​

  • Load and preprocess data

  • Create topographic maps with different methods

  • Customize time intervals and appearance

Epoched Data ​

  • Extract epochs from continuous data

  • Plot topographies for specific epochs

  • Customize interpolation and display

ERP Data ​

  • Average epochs into ERPs

  • Create condition-specific topographies

  • Control colorbar placement

Multi-Panel Figures ​

  • Create custom figure layouts

  • Combine multiple topographies

  • Control colorbar positions for each plot

Code Examples ​

Show Code
julia
# Demo: Topographic Maps
# Shows scalp topography visualization for ERP data and components.

# Note: EegFun.example_path() resolves bundled example data paths.
# When using your own data, simply pass the file path directly, e.g.:
# dat = EegFun.read_raw_data("/path/to/your/data.bdf")

using EegFun
using GLMakie

# read raw data
dat = EegFun.read_raw_data(EegFun.example_path("data/bdf/example1.bdf"));

# read and prepare layout file
layout = EegFun.read_layout(EegFun.example_path("layouts/biosemi/biosemi72.csv"));
EegFun.polar_to_cartesian_xy!(layout)

# create EegFun data structure (EegFun.ContinuousData)
dat = EegFun.create_eegfun_data(dat, layout);

# Some minimal preprocessing (average reference and highpass filter)
EegFun.rereference!(dat, :avg)
EegFun.highpass_filter!(dat, 1)

# visually selected blink like artifact via interval selection times
with_theme(Theme(colormap=:coolwarm)) do
EegFun.plot_topography(dat, interval_selection = EegFun.times(5.973, 6.02), ylim = (-200, 200))
end

EegFun.plot_topography(dat, interval_selection = EegFun.times(6), ylim = (-200, 200))

# blink like artifact via sample selection predicate
EegFun.plot_topography(dat, sample_selection = x -> x.time .>= 5.973 .&& x.time .<= 6.02, ylim = (-200, 200))

# blink like artifact across multiple time points
EegFun.plot_topography(dat, sample_selection = x -> x.time .>= 5.5 .&& x.time .<= 6.5, ylim = (-75, 75), n_topo = 5, dims = (1, 5))
EegFun.plot_topography(
    dat,
    sample_selection = x -> x.time .>= 5.5 .&& x.time .<= 6.5,
    ylim = (-75, 75),
    n_topo = 5,
    dims = (1, 5),
    colorbar_plot_numbers = 5,
)

# Various combinations
EegFun.plot_topography(dat, colorbar_plot = false, head_radius = 1.25)
EegFun.plot_topography(dat, gridscale = 250)
EegFun.plot_topography(dat, colormap = :inferno)
EegFun.plot_topography(dat, colormap = :redblue)
EegFun.plot_topography(dat, plot_title = "Custom Title", plot_title_fontsize = 30)
EegFun.plot_topography(dat, sample_selection = x -> x.time .>= 0.4 .&& x.time .<= 0.6)
EegFun.plot_topography(dat, sample_selection = x -> x.time .>= 0.4 .&& x.time .<= 0.6, method = :spherical_spline)
EegFun.plot_topography(dat, channel_selection = EegFun.channels([:Fp1, :Fp2, :Cz]))
EegFun.plot_topography(dat, colorbar_kwargs = (; size = 20, position = (2, 1), vertical = false))

#################################
# Epoched DataFrameEeg
#################################
# some epoched data
epoch_cfg = [
    EegFun.EpochCondition(name = "ExampleEpoch1", trigger_sequences = [[1]]),
    EegFun.EpochCondition(name = "ExampleEpoch2", trigger_sequences = [[2]]),
]
epochs = EegFun.extract_epochs(dat, epoch_cfg, (-2, 4))

# Separate plots
EegFun.plot_topography(epochs[1], 1) # Condition 1, Epoch 1
EegFun.plot_topography(epochs[2], 1) # Condition 2, Epoch 1
EegFun.plot_topography(epochs, ylim = (-0.1, 0.1)) # NOTE: Consider adding aspect ratio and global scale controls in the future
EegFun.plot_topography(epochs, sample_selection = x -> x.time .>= 0.4 .&& x.time .<= 0.6)



#################################
# ERP like data
#################################
erps = EegFun.average_epochs(epochs)

EegFun.plot_topography(erps, sample_selection = x -> x.time .>= 0.4 .&& x.time .<= 0.6, ylim = (-2, 2), time_unit = :ms)
EegFun.plot_topography(erps, interval_selection = (0.4, 0.6), ylim = (-2, 2))

EegFun.plot_topography(erps, interval_selection = (0.4, 0.6), ylim = (-2, 2), colorbar_plot_numbers = [1, 2])

EegFun.plot_topography(
    erps,
    interval_selection = (0.4, 0.6),
    ylim = (-2, 2),
    colorbar_plot = true,
    colorbar_kwargs = (; position = (2, 1), vertical = false),
)

EegFun.plot_topography(erps)
EegFun.plot_topography(erps, ylim = (-2, 2))
EegFun.plot_topography(erps[2])
EegFun.plot_topography(erps[1], gridscale = 50)
EegFun.plot_topography(erps[2], gridscale = 1000)
EegFun.plot_topography(erps[1], colormap = :inferno)
EegFun.plot_topography(erps[2], plot_title = "Custom Title", plot_title_fontsize = 30)

See Also ​