diff --git a/docs/src/general.md b/docs/src/general.md
index 7703282..4529631 100644
--- a/docs/src/general.md
+++ b/docs/src/general.md
@@ -15,6 +15,7 @@ The recipe supports different interpolation methods, namely:
 ```@docs
 TopoPlots.ClaughTochter
 TopoPlots.SplineInterpolator
+TopoPlots.NullInterpolator
 ```
 One can define your own interpolation by subtyping:
 
diff --git a/src/core-recipe.jl b/src/core-recipe.jl
index 0f1b85a..66c7ff3 100644
--- a/src/core-recipe.jl
+++ b/src/core-recipe.jl
@@ -5,6 +5,7 @@
         sensors = true,
         interpolation = ClaughTochter(),
         bounding_geometry = Circle,
+        markersize = 5,
         padding = 0.1,
         pad_value = 0.0,
         resolution = (512, 512),
@@ -27,6 +28,7 @@ Creates an irregular interpolation for each `data[i]` point at `positions[i]`.
 * `labels::Vector{<:String}` = nothing: names for each data point
 * `interpolation::Interpolator = ClaughTochter()`: Applicable interpolators are $(join(subtypes(TopoPlots.Interpolator), ", "))
 * `bounding_geometry = Circle`: the geometry added to the points, to create a smooth boundary. Can be `Rect` or `Circle`.
+* `markersize = 5`: size of the points defined by positions
 * `padding = 0.1`: padding applied to `bounding_geometry`
 * `pad_value = 0.0`: data value filled in for each added position from `bounding_geometry`
 * `resolution = (512, 512)`: resolution of the interpolation
@@ -124,7 +126,7 @@ function Makie.plot!(p::TopoPlot)
         contour!(p, xg, yg, data; attributes...)
     end
     label_scatter = to_value(p.label_scatter)
-    attributes = @plot_or_defaults label_scatter Attributes(markersize=5, color=p.data, colormap=p.colormap, colorrange=p.colorrange, strokecolor=:black, strokewidth=1)
+    attributes = @plot_or_defaults label_scatter Attributes(markersize=p.markersize, color=p.data, colormap=p.colormap, colorrange=p.colorrange, strokecolor=:black, strokewidth=1)
     if !isnothing(attributes)
         scatter!(p, p.positions; attributes...)
     end
diff --git a/src/interpolators.jl b/src/interpolators.jl
index 7c5b3b4..367100b 100644
--- a/src/interpolators.jl
+++ b/src/interpolators.jl
@@ -101,3 +101,20 @@ end
 #     # the xg' * ones is a shorthand for np.meshgrid
 #     return xg, yg, interp.set_locations( ones(length(xg))' .* yg, xg' .* ones(length(yg)))()
 # end
+
+
+"""
+    NullInterpolator()
+
+Interpolator that returns "0", which is useful to display only the electrode locations + labels
+"""	
+struct NullInterpolator <: TopoPlots.Interpolator
+	    
+end
+
+function (ni::NullInterpolator)(
+        xrange::LinRange, yrange::LinRange,
+        positions::AbstractVector{<: Point{2}}, data::AbstractVector{<:Number})
+  
+    return zeros(length(xrange),length(yrange))
+end
diff --git a/test/runtests.jl b/test/runtests.jl
index 4447bb3..82050dd 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -24,6 +24,11 @@ begin
     @test_figure("all-interpolations", f)
 end
 
+begin # empty eeg topoplot
+    f, ax, pl = TopoPlots.eeg_topoplot(1:length(TopoPlots.CHANNELS_10_20),TopoPlots.CHANNELS_10_20; interpolation=TopoPlots.NullInterpolator(),)
+    @test_figure("nullInterpolator", f)
+end
+
 # begin
 #     f = Figure(resolution=(1000, 1000))
 #     s = Slider(f[:, 1], range=1:size(data, 2), startvalue=351)
@@ -72,3 +77,4 @@ begin
     f, ax, pl = eeg_topoplot(data[:, 340, 1]; positions=positions)
     @test_figure("eeg-topoplot3", f)
 end
+