diff --git a/src/configs.jl b/src/configs.jl
index 7bd40645..1f341f75 100644
--- a/src/configs.jl
+++ b/src/configs.jl
@@ -5,7 +5,7 @@
 Default configurations for the supporting axis. Similar to PlotConfig, but these configurations are not shared by all plots.\\
 Such supporting axes allow users to flexibly see defaults in docstrings and manipulate them using corresponding axes.
     
-For developers: to make them updateable in the function, use `update_axis`.
+For developers: to make them updateable in the function, use `update_axis`.\\
 **Return value:** `NamedTuple`.
 """
 function supportive_defaults(cfg_symb::Symbol)
diff --git a/src/pattern_detection.jl b/src/pattern_detection.jl
index b45db6df..172409f4 100644
--- a/src/pattern_detection.jl
+++ b/src/pattern_detection.jl
@@ -7,23 +7,23 @@ For instance, single EEG channel (sensor) with trials over time.\\
 Method:\\
 - Filter dataset for smearing.\\
 - Use pattern detection function.\\
-- In "plot" mode returns an ERP image with a value of pattern detection. Otherwise - only value.
+- In `mode = "plot"` returns an ERP image with a value of pattern detection. Otherwise - only value.
 
 ## Arguments
 
-- erp_data::Matrix{Float64}`\\
+- `erp_data::Matrix{Float64}`\\
     3-dimensional array of voltages of event-related potentials. Dimensions: channels, recording time, trials. 
-- detector::Function`\\
+- `detector::Function`\\
     Function used for pattern detection.\\
     For example, `Images.entropy` from `Images.jl`.
-- filter::Function`\\
+- `filter::Function`\\
     Function used for smearing.\\
 
 ## Keyword arguments (kwargs)
-- mode::String = "plot"` \\
+- `mode::String = "plot"` \\
     Plot an ERP image with the pattern detection value.
 
-**Return Value:** (Figure with) pattern detection value.
+**Return Value:** (`Figure` with) pattern detection value.
 """
 function pattern_detector(
     erp_data::Matrix{Float64},
@@ -64,17 +64,17 @@ Mode of permuted means:\\
 
 - `erp_data::Array{Float64, 3}`\\
     3-dimensional Array of voltages of Event-related potentials. Dimensions: time of recording, trials, channels. 
-- detector::Function`\\
+- `detector::Function`\\
     Function used for pattern detection.\\
     For example, `Images.entropy` from `Images.jl`.
-- filter::Function`\\
+- `filter::Function`\\
     Function used for smearing.\\- `kwargs...`\\
     Additional styling behavior. \\
 
 ## Keyword arguments (kwargs)
 - `n_permutations::Number = 10` \\
     Number fo permutations. Useful for mode "permuted_means" where it defines number of random permutations before averaging.
-- mode::String = "basic"` \\
+- `mode::String = "basic"` \\
     With the "permuted_means" mode, results are given as the absolute value between the detector result over the given data set and the randomly permuted data set.
 
 **Return Value:** DataFrame with pattern detection values. Dimensions: experimental events, channels.
diff --git a/src/pattern_simulation.jl b/src/pattern_simulation.jl
index a5e65875..6ad17dab 100644
--- a/src/pattern_simulation.jl
+++ b/src/pattern_simulation.jl
@@ -130,7 +130,7 @@ Columns in resulting sim\\_6patterns Data Frame to simulate this patterns: Δlat
 - `σ::Float = 3.2`\\
     Controls standart deviation.
 
-**Return Value:** sim\\_6patterns::Matrix{Float64} with voltages and sim_evts::DataFrame with events. 
+**Return Value:** `sim\\_6patterns::Matrix{Float64}` with voltages and `sim_evts::DataFrame` with events. 
 """
 function simulate_6patterns(μ = 3.2, σ = 0.5; tmp = nothing)
     design = SingleSubjectDesign(;